esa-sceva/satcom-chunk-collection huggingface dataset:
## 6 Discussion  
After the frequency-Bessel method adopted in the paper was proposed, exciting results have been achieved in recent years in the large-scale imaging of the shear wave velocity structure of the Kanto Basin in Japan [43] and the three-dimensional shear wave velocity structure in the continental United States [44,45]. Although some scholars have made some attempts to study the frequency-Bessel method in detecting shallow geological structures, there have been no reports of combining the frequency-Bessel method with karst exploration. Compared to the background noise surface wave method, the use of the multi-channel surface wave method in detecting railway hazards [46,47] has achieved certain results. Due to the significant noise interference in the urban environment of the study area in the paper, it is difficult to collect high-quality raw data by conventional geophysical methods, including multi-channel surface wave technology. Therefore, surface wave analysis based on background noise will be very meaningful for karst detection.  
The karst development area studied in the paper was previously explored by the high-density resistivity method, and the interpreted anomaly location of karst [48] is very consistent with the results of the joint inversion using multi-mode dispersion in the paper. However, the use of multi-mode dispersion information has a higher lateral resolution of karst and is more effective in vertical stratification, which verifies the feasibility and correctness of karst imaging based on multi-mode dispersion.  
Due to the low detection efficiency and relatively high construction difficulty of the high-density resistivity method, the data are easily disturbed by external interference. In comparison, using the background noise as the signal source, the fundamental and higher-mode dispersion curves can be extracted through the frequency-Bessel transform, and then the S-wave velocity structure of strata can be inverted, making it easier to achieve in data acquisition and processing.  
In addition, according to the interpretation results [49] of ground penetrating radar carried out in the work area, there are discontinuous stripes in the profile, accompanied by small arc-shaped reflections in some areas, and multiple reflections in the karst area, indicating that ground penetrating radar has a certain sensitivity to karst. However, compared to the 90 m depth of inversion through the frequency-Bessel transform in the paper, the abnormal location reflected by ground penetrating radar is shallow, and the detection effect is greatly affected by surface conditions [50]. Therefore, the method has strong applicability, does not require the arrangement of active sources like other geophysical methods, and can achieve good results in noise-rich urban environments.
## 1 Introduction
This design enhances inter-channel information fusion while preserving spatial structure, thus improving adaptability in various environments. Furthermore, we introduce a cross-image correlation-aware representation mechanism, which computes relationships between feature embeddings across multiple images within a training batch, thus enhancing global descriptor robustness. Our key contributions can be summarized as follows:  
1. Global descriptor generation with cross-image information--We introduce a novel global descriptor generation approach that integrates cross-image information with optimal transport-based feature aggregation, thus enhancing recognition robustness. 2. Parameter-efficient adaptation strategy--We propose a lightweight adaptation mechanism that decouples spatial filtering via depthwise convolutions from channel-wise interactions via pointwise convolutions. This design reduces the computational overhead (FLOPs) compared to other conventional adapters. 3. State-of-the-art performance--Extensive experiments conducted on multiple VPR benchmarks demonstrate that CriSALAD outperforms existing approaches on several datasets, such as Pitts30k and Nordland. The remainder of this paper is organized as follows. Section 2 provides a review of related works in the fields of VPR and parameter-efficient transfer learning. Section 3 begins with a brief overview of transformer blocks, followed by a detailed presentation of our proposed method, CriSALAD. This includes the design of the VPR framework, which integrates depthwise separable convolution adaptation, global descriptor aggregation, and a cross-image method. The experimental details and results are discussed in Section 4. Finally, this paper concludes in Section 5.
## 3 Materials and Methods
### The 5G-Specialized Satellite Platform  
This is constituted by the onboard 5G-specialized Satellite Terminal (5 ST), a transceiver guaranteeing connectivity in the open sea via a Ku-band GEO satellite link, and on the ground side by the 5G-specialized Satellite Gateway (5 SG). The former includes the IP optimizer software module, which implements the optimization algorithm (including compression and aggregation). The latter performs demodulation and Layer-2 functionalities. Furthermore, for the 5 SG component, some virtualized network functions (i.e., routing) were deployed as software modules running on commercial servers in the cloud. This introduced the flexible, dynamic and programmable 5G network paradigm in the 5 GT System. Moreover, SDN was deployed in the satellite teleport network to steer the traffic through SDN switches. In this way, the massive data flow data at the passage of the ship from near sea to open sea scenario can be efficiently handled, and the real-time requirements, when the handover between the maritime and the terrestrial domains occurs, are met.
# Model Predictive Control of Running Biped Robot
## 5 Performance Validation
### Simulation Environment  
A simulation model based on our biped robot called HYBRO (Hanyang Biped Robot) is created as shown in Figure 6. The total weight of the robot model was about 33 kg and the weight of the upper body including the arms was about 18 kg. The height of the robot was 1.15 m and the height of the hip was 0.625 m. All of its parameters computed from CAD data of HYBRO are summarized in Table 1. This model has 28 DOFs; however, just 6 DOFs of the lower body were used and other joints were fixed for the simulations in a 2D environment.  
A model of contact between the supporting foot and the ground is very important for more realistic simulations. In this paper, the Hunt-Crossley model was used [40], where the vertical component of the GRF was computed by  
\[F_{n}=k\delta^{m1}+c\frac{\delta}{|\delta|}|\delta|^{m_{2}}\delta^{m_{3}}, \tag{36}\]  
where \(k\) and \(c\) denote the spring and damping coefficients, respectively; \(\delta\) denotes the amount of deformation at the foot on the ground; and \(m_{1}\), \(m_{2}\) and \(m_{3}\) respectively denote the stiffness, damping, and indentation exponents. The horizontal component of the contact force was calculated as  
\[F_{f} = \mu(\
u)|F_{n}|, \tag{37}\]  
where \(\mu(\
u)\) is the friction coefficient depending on slip velocity, \(\
u\). The coefficient is calculated based on the offered friction model by RecurDyn [41; 42] with \(\
u_{s}\), \(\
u_{d}\), \(\mu_{s}\), and \(\mu_{d}\), where \(\
u_{s}\) and \(\
u_{d}\) are respectively the static and dynamic threshold velocities; and \(\mu_{s}\) and \(\mu_{d}\) respectively denote the static and dynamic friction coefficients. The numerical values of all these parameters used in the simulations are summarized in Table 2.  
To verify the performance of the proposed algorithm, simulations of the running of a biped robot in several different environments were carried out. Firstly, the biped robot running on flat terrain was simulated to show that the velocity of the robot was controlled well with the proposed method. Secondly, to confirm the adaptability to the uncertainties in the environment, simulations for running on unobserved uneven terrains were performed.  
All the simulations used an identical scenario as follows. Firstly, the robot bent its knees 55 degrees to avoid kinetic singularity at \(t=1.1\) s, such that the hip was located at 0.4 m from the ground and the forward lean angle of the upper body was 7.5 degrees. Afterward, the robot started running to reach the target speed. Until \(t=1.8\) s, the reference speed in the horizontal direction of the support phase is 0 m/s, afterwards, it is increased gradually to the target speed.
## 3 Results
### Gray Correlation Analysis Results
#### 3.3.2 Carbon Emissions and the Correlation of Urban Spatial Extension  
Similarly, the correlations between the five indicators of carbon emissions and the intensity of land expansion (\(I\)), urban morphology indices (\(SBC\)), urban compactness (\(U\)) and shortest travel distance (\(Z\)) were calculated. The results of the calculation are shown in Table 7. All five indicators of carbon emissions have some correlation with the shortest travel distance. The correlation between the shortest travel distance and total carbon emissions and per capita emissions is the highest, 0.992 and 0.963, respectively, which is close to 1. The correlation between shortest travel distance and carbon-emission intensity and carbon emission per unit of land is the second highest, \(-0.613\) and 0.666, respectively. The carbon emission growth rate and urban land expansion intensity also have a high correlation, with an index of 0.669.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Relational Grades**} & \multicolumn{5}{c}{**Correlation with Land Expansion Intensity**} \\ \cline{2-6}  & **R** & **A\&B** & **M** & **S** & **G** \\ \hline Total carbon emissions (TCE) & 0.999 & 0.938 & 0.967 & 0.962 & \(-0.984\) \\ Per capita emissions (PCE) & 0.978 & 0.946 & 0.932 & 0.95 & \(-0.961\) \\ Emission growth rate (EG) & 0.788 & 0.549 & 0.168 & \(-0.148\) & 0.906 \\ Carbon-emission intensity (EI) & \(-0.621\) & \(-0.844\) & \(-0.634\) & \(-0.723\) & \(-0.613\) \\ Emission per unit land (EPL) & 0.678 & 0.554 & 0.538 & 0.634 & 0.667 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Relational grades of the carbon emissions index and urban land use area.  
There was a negative correlation between total carbon emissions and carbon emissions per capita with the urban form index and urban compactness. It has a stronger correlation with the urban form index at \(-0.827\) and \(-0.834\), respectively. Its correlation with urban compactness is \(-0.392\) and \(0.482\), respectively, which is weaker than the former. The correlation between carbon-emission intensity and urban form compactness is stronger, with a correlation coefficient of \(0.858\). The correlation between carbon emissions per unit of land and the urban form index is stronger, with a correlation coefficient of \(0.707\). The smaller the urban form index and the more compact the city, the lower the carbon-emission intensity.
# Worldwide Coverage Mobile Systems for
## 4 Ku-Band Antennas Design Techniques
### Wave-Frontier Toroidal Antenna  
Another type of antenna shown in Figure 4, which in shape is similar to the Gregory reflector, is the called dual reflector toroidal antennas. The main difference is the key concept used to design this antenna: the sub-reflector of the toroidal antenna is part of the virtual toroid while the main reflector is shaped like an ellipsoid.  
This antenna uses a convex-concave shaped sub-reflector, i.e., it is convex in one of the planes while in the other it is concave. The main drawback of this type of antenna is the complex mathematical computation required to its design and the mechanical implementation. New technologies and CAD (Computer-Aided Design) make these tasks much easier and accurate. Size and weight make difficult the use of these antennas for worldwide mobile communications.
## 4 Simulations
### System Description  
The following simulation adopted the model of a 9 DOF hyper-redundant manipulator with an eye-in-hand camera. This 9 DOF manipulator was independently designed and manufactured by our laboratory. Figure 4 shows the mechanical structure and schematic of this manipulator, and Table 1 gives the Denavit-Hartenberg parameters of the manipulator.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Joint** & \(\mathbf{q_{n}}\) & \(\mathbf{\alpha_{n-1}}\) & \(\mathbf{a_{n-1}}\) & \(\mathbf{d_{n}}\) & **Joint Limit** \\ \hline
1 & q1 & 0 & 0 & 0 & \(\pm 90^{\circ}\) \\
2 & q2 & \(90^{\circ}\) & 165.5 & 0 & \(\pm 90^{\circ}\) \\
3 & q3 & \(-90^{\circ}\) & 165.5 & 0 & \(\pm 90^{\circ}\) \\
4 & q4 & \(90^{\circ}\) & 165.5 & 0 & \(\pm 90^{\circ}\) \\
5 & q5 & \(-90^{\circ}\) & 165.5 & 0 & \(\pm 90^{\circ}\) \\
6 & q6 & \(90^{\circ}\) & 165.5 & 0 & \(\pm 90^{\circ}\) \\
7 & q7 & \(-90^{\circ}\) & 165.5 & 0 & \(\pm 90^{\circ}\) \\
8 & q8 & \(90^{\circ}\) & 165.5 & 0 & \(\pm 90^{\circ}\) \\
9 & q9 & \(-90^{\circ}\) & 165.5 & 0 & \(\pm 90^{\circ}\) \\ \hline \hline \end{tabular}
\end{table}
Table 1: Denavit–Hartenberg parameters of the nine degree-of-freedom (9 DOF) manipulator.  
Figure 4: Manipulator structure and link coordinate systems of the 9 DOF manipulator.  
A five-megapixel industrial camera was mounted at the end-effector, and its intrinsic parameter was  
\[K=\left(\begin{array}{ccc}1132.1&0&1280\\ 0&1132.1&1024\\ 0&0&1\end{array}\right).\]  
To simplify the system model, the camera frame \(F\) was considered to coincide with the end-effector frame \(F_{e}\).
# Low-Cost, Distributed Environmental Monitors for Factory Worker Health
## 3 Results and Discussion
### Carbon Monoxide Sensors  
Figure 6 illustrates the average concentration of 30 sensors and their standard deviations relative to the Q-Trak Plus 8552 reference instrument during the CO decay experiment. The leveling off indicates that, for the selected gain on the monitor board, the low-cost CO sensors were saturated for concentrations above 15 ppm. Therefore, we performed linear regression comparing measurements from the low-cost CO sensors and the Q-Trak Plus 8552 for concentrations below 15 ppm, and the average slope, intercept, and \(R^{2}\) were equal to 0.85, \(-\)1.3 ppm, and 0.99, respectively. For the span gas experiment, the bias values varied from 4% to 27%, and the precision for all monitors was 5%.  
Figure 5: Sharp DN mV outputs for each monitor (\(n=30\)) relative to the particulate mass reported by the reference aerosol monitor for varying levels of salt concentrations.  
The CO sensors in the monitors are limited to concentration values below 15 ppm. This is low relative to the OSHA recommended time-weighted average value of 50 ppm [54], but sufficient for the expected levels of carbon monoxide in the setting we were investigating. The correlation was high among the CO sensors, suggesting that the average calibration constants derived for all sensors were adequate [40]. The bias variability may be related to the fact that we used an average slope and intercept for all the sensors, where in reality, each sensor has its unique slope and intercept.
## 3 Results and Discussions
### Performance Grade (PG)  
The rutting resistance parameter G*/Sin of the un-aged and RTFO-aged MMBs are shown in Tables 8 and 9, respectively. The G*/Sin of the MMBs versus temperature effects were plotted, as shown in Figures 5 and 6. The results were compared with the rheological parameter (G*/Sin) of the control PG [50].  
Figure 5: Performance grade (PG) limit for un-aged binders.  
Figure 6: PG grade limit for rolling thin film oven (RTFO)-aged binders.  
The test results of the un-aged binder show an improvement in the performance grade from the control PG58 to PG64 in all MMBs, while those of RTFO-aged improved to PG-70. This result indicates that partially replacing bitumen with sugarcane molasses could increase the stiffness and rheological parameters of the resulting blended binder. Complex shear modulus was increased due to the addition of molasses and RTFO-aging. The increment in the complex shear modulus could mean an improvement in the rutting performance of the binder. To confirm this increment quantitatively, rutting resistance parameters (G*/sin8) of the unagedMMB5, MMB10, MMB15, and MMB20 were increased by 38.02%, 20.32%, 11.98%, and 11.46%, respectively, at a temperature of 58 \({}^{\circ}\)C and by 48.67%, 29.8%, 29.76%, and 20.7%, respectively, at 64 \({}^{\circ}\)C. The RTFO-aged samples became stiffer, which led to an increased rutting resistance factor. However, [PERSON] [51] reported that there is a weak relationship between the stiffness parameter (G*/sin8) and rutting potential and recommend the multiple stress creep recover test for a strong relationship and to measure the rutting potential accurately [51]. Therefore, the MSCR test was performed to measure the rutting performance and correlate the result with strategic highway research program performance grade (SHRP-PG) [52].
# Tamper and Clone-Resistant Authentication Scheme for Medical Image Systems
## 4 A Proposed New Secured Unclonable Medical Watermarking Scheme
### The Proposed Embedding and Extraction of Clone-Resistant Watermarking  
The proposed system has two main phases: First, generating and embedding a signed watermark into the original image. Second, extracting the watermark and using it to verify the authenticity and integrity of the watermarked image. These two phases are described as follows:
# A Novel Hybrid Approach to Deal with DVL Malfunctions for Underwater Integrated Navigation Systems
###### Abstract  
As a common device for underwater integrated navigation systems, Doppler velocity log (DVL) has the risk of malfunction. To improve the reliability of navigation systems, a hybrid approach is presented to forecast the measurements of the DVL while it malfunctions. The approach employs partial least squares regression (PLSR) coupled with support vector regression (SVR) to build a hybrid predictor. As the current and past calculating velocities of strapdown inertial navigation system (SINS) are taken as the predictor's inputs, PLSR is applied to cope with the situation where there exists intense relativity among independent variables. Since PLSR is a linear regression, SVR is used to predict the residual components of the PLSR prediction to improve the accuracy. When the DVL works well, the hybrid predictor is trained online as a backup, whereas during malfunctions, the predictor offers the estimation of the DVL measurements for information fusion. The performance of the proposed approach is verified with simulations based on SINS/DVL/MCP/pressure sensor (PS) integrated navigation system. The comparison results indicate that the PLSR-SVR hybrid predictor can correctly provide the estimated DVL measurements and effectively extend the tolerance time on DVL malfunctions, thereby improving the navigation accuracy and reliability.  
strAPdown inertial navigation system (SINS); Doppler velocity log (DVL); integrated navigation; predictor; partial least squares regression (PLSR); support vector regression (SVR)
## 3 Results and Discussion
### Laboratory Artificial Patinas on Copper Specimens  
The chemical procedures employed for the realisation of the laboratory artificial patinas were selected to reproduce the most common natural corrosion products that are formed on copper-based surfaces upon exposure to outdoor environment.  
Concerning the Cuprite patinas, three different patination procedures were adopted for the production of cuprite patinas. These were immersion in a \"boiling\" solution of CuSO4-5H2O, Cu(CH3 COO)2 NaCl and KNO3 [51], or by wet and dry cycles in artificial seawater and in deionised water to promote the oxidation of the surfaces.  
Concerning the \"boiling solution\" cuprite, it appears \"reddish\", uniform, and homogeneous from a macroscopic point of view, and looks well adherent to the metallic substrate (Figure 6a). The specimens that underwent wet and dry cycles in deionised water, instead, showed the formation of a dark and compact brown patina (Figure 6b), with an aspect quite similar to the one observed also for naturally formed cuprite. However, such corrosion layer appeared scarcely uniform, and several areas of the specimens still showed the shiny surface of the copper substrate. This is particularly evident when observing the specimens in stereomicroscopy (Figure 7a).  
Figure 6: Pictures of copper specimens with cuprite patina produced by: (**a**) immersion in “boiling solution”; (**b**) wet and dry cycles in deionised water; (**c**) wet and dry cycles in artificial seawater.  
Figure 7: Stereomicroscopy image of specimen with cuprite patina obtained (**a**) by wet and dry cycles in deionised water, (**b**) by wet and dry cycles in artificial seawater.  
The copper specimens that underwent wet and dry cycles in artificial seawater (3.5% NaCl in water), instead, appear completely covered by a dark brown-reddish layer, which appears macroscopically uniform and well adherent to the substrate. However, if such specimens are observed by stereomicroscopy (Figure 7b), the presence of small greenish crystals can be observed. In this case, however, such patination procedure appeared quite aggressive, causing a thickness loss of the patinated surfaces significantly higher compared to the other two procedures described for the realisation of cuprite.  
The compositional characterisation by means of FTIR spectroscopy confirmed the presence of cuprite, which characteristic peak is visible around 600 cm\({}^{-1}\), on all the specimens previously described [100]. In particular, cuprite was the only compound detected on specimens patinated by immersion in \"boiling solution\" and on those immersed in deionised water. On the specimens patinated with artificial seawater, instead, the main peaks of paratacamite are also visible at 3445 cm\({}^{-1}\), 3355 cm\({}^{-1}\) and 3305 cm\({}^{-1}\)[100, 116]. The presence of such compound, due to the employment of NaCl in the patination solution, was already suggested by the presence of the green crystals observed by stereomicroscopy.
# Analysis of Video Transmission Capabilities in a Simulated OFDM-Based Supplementary BPL-PLC System
## 4 Results
As observed, the degree of distortions and interference was at the threshold of acceptability. Yet, as pointed out by the group of viewers, for higher SNR values, the most important visual information could be pinpointed out and tracked effectively. To sum up, for the lowest SNR equal to 24 dB, the quality was very poor. No details were visible, colors were distorted and numerous elements did not have sharp edges (grainy and/or blurred). For instance, the first (walking man) and second (cars) sequence was easily interpreted, whereas the third one (windmill) presented something hard to determine. In the case of the fourth and fifth sequences (toddler), people reported not knowing whether it was just noise or not. The second level of the SNR equal to 24.4 dB provided similar observations, as no changes were noticeable. The third level of the SNR equal to 27 dB was ranked definitely better compared to previous ones. Yet, the quality was still unacceptable, as many pixel artefacts occurred. As reported, there was a visible decrease in the level of noise, the shapes were more precise, i.e., the windmills were adequately labeled, just like the fountains. In the fourth level of SNR equal to 28.3 dB there was a noticeable upgrade; however, the color mismatch and artefacts among many pixels were still present. For the second highest level of SNR equal to 28.7 dB, the level of noise, artefacts and color distortions was smaller. The highest level of SNR equal to 29 dB was ranked evidently better than the previous ones.