esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Numerical Experiments and Analysis
### Hybrid Algorithm Based on CC-SHADE-ML and MTS-LS1  
In the CC-SHADE-ML algorithm, MTS-LS1 [41] performs after the optimization cycle and uses 25,000 FEs (this value has been defined by numerical experiments). MTS-LS1 tries to improve each \(i\)-th coordinate using the search range SR[i]. In this study, the initialization value of each SR[i] is equal to \((b_{i}-a_{i})\cdot\)0.4. \(a_{i}\) and \(b_{i}\) are low and high bounds for the \(i\)-th variable. If MTS-LS1 does not improve a solution using the current value of SR[i], it should be reduced by two times (SR[i] = SR[i]/2). If SR[i] is less than \(10^{-18}\) (in [41], the original threshold is \(10^{-15}\)), the value is reinitialized. As we can see from the numerical experiments, usually, MTS-LS1 finds a new best solution that is so far from other individuals in the population. Thus, CC-SHADE-ML is not able to improve the best-found solution after applying MTS-LS1, but it does improve the median fitness value in the population. In this case, Formula (2) will be inappropriate for the evaluation of the performance of selected parameters. We use Formula (4) to overcome this difficulty, the formula is based on the median fitness value before and after the CC-SHADE-ML cycle. \[performance_{i}=\frac{medianFitness_{before}-medianFitness_{after}}{medianFitness_{ before}} \tag{4}\]  
Different mutation schemes have been evaluated and we determined that the best performance of CC-SHADE-ML-LS1 has been reached using the following Formula (5). \[u_{i}=x_{i}+F_{i}\Big{(}x_{pbest}-x_{i}\Big{)}+F_{i}(x_{t}-x_{r}),\ i=1,\dots, pop\_size \tag{5}\]  
here, \(u_{i}\) is a mutant vector, \(x_{i}\) is a solution from the population, \(F_{i}\) is a scale factor, \(x_{pbest}\) is a solution from the population chosen from the \(p\) best solutions, \(x_{t}\) is a solution from the population chosen using the tournament selection (in this study, the tournament size is equal to 2), \(x_{r}\) is a randomly chosen solution from the population or from the archive. To perform Formula (5), the following condition must be met: \(i\
eq pbest\
eq t\
eq r\). Control parameters of CC-SHADE-ML-LS1 are the following: the set of subcomponents equal to {5, 10, 20, 50}; the set of the population size equal to {25, 50, 100}; FEs_LS1 equal to 25,000; the mutation scheme, in SHADE, is (5); and the tournament size is 2. FEs_cycle_init is equal to \(1.5\times 10^{5}\). The complete pseudocode of the hybrid is presented in Algorithm 3. Additionally, the CC-SHADE-ML-LS1 performance has been evaluated and compared with state-of-the-art metaheuristics. Comparison rules and algorithms for comparison are the same as in Section 3.2. Tables 11 and 12 have the same structure as Tables 9 and 10, respectively. Table 11 shows the ranking of CC-SHADE-ML-LS1. Table 12 contains the detailed results of the tuned CC-SHADE-LS1 algorithm. Figure 10 has the same structure as Figure 9.  
Figure 9: The ranking of CC-SHADE-ML and other state-of-the-art algorithms.
## 3 Results
### Comparative Performance Context  
Despite U-Net achieving the highest performance among the evaluated models, the overall Dice coefficients (approximately 0.63-0.66) remained notably lower than those typically reported for segmentation of larger abdominal organs such as kidneys or liver, where Dice scores commonly exceed 0.85. This performance gap reflects the increased segmentation complexity associated with the small size, irregular morphology, and anatomical proximity of adrenal glands to high-contrast structures.  
Important Note: The precision, sensitivity, specificity, and HD95 values reported in this study were approximated based on expected patterns from the Dice similarity coefficient and typical performance behavior observed in small-organ segmentation tasks. These metrics were not directly computed from the raw segmentation outputs.
## 4 Fault-Tolerance Control Strategy
### Simulation Verification
#### 4.4.2 Three Motors Fault Working Conditions  
The vehicle was tracked in typical operating conditions, and at 2 s, the triple steering motors failed, at which point it went into emergency braking.  
From Figure 18, it can be seen that in 2 s when there is vehicle right front, right rear, left rear wire-controlled steering motor failure, at this moment in time the vehicle, according to the fault-tolerant decision-making instructions for emergency braking, quickly reaches the maximum 10 MPa in the four wheels of the wheel cylinder pressure, as shown in Figure 18c; in Figure 18d, the vehicle speed in the implementation of emergency braking can be seen. The vehicle speed slows down quickly in 2 s from 85 km/h down to 0 km/h, so that the vehicle stops in the shortest possible time to ensure the security of the vehicle.  
Figure 17: Single motor fault simulation results. (**a**) Graph of transverse displacement; (**b**) Graph of yaw angle; (**c**) Motor torque diagram; (**d**) Wheel turning angle comparison chart.
## 3 Results and Discussion
### Investigation of AE under Tension of Specimens with Dissimilar Welded Joints
Therefore, it can be assumed that the additional maximum of the AE hits rate is an indicator of a decarburized diffusion interlayer. Figure 5: Results of dissimilar defect-free welded joint test: AE data recorded under tension (**a**), sample with a painted area (**b**), and strain distributions over the painted area on different stages of test (**c**,**d**). A sign of a brittle carbide interlayer can be a change in the parameters of the distribution of the AE hits amplitudes. Figure 9 shows the distributions of the AE hits amplitudes for a defect-free specimen made from a plate that has not undergone heat treatment (Figure 9a) and a specimen with a confirmed presence of diffusion interlayers (Figure 9b). The distributions were plotted over the interval corresponding to the strain-hardening section of the tension diagram, where the parameters of the AE hits change, predominantly stationarily. In the presence of diffusion interlayers, the distribution has a pronounced tail of high-amplitude values reaching 75-80 dB. Figure 6: AE data recorded under tension of a specimen of a dissimilar welded joint with a lack of penetration. Figure 7: Distribution of time intervals between the adjacent AE hits. (**a**) For defect-free dissimilar weld specimen, and (**b**) for dissimilar weld specimen with lack of penetration. Figure 8: Results of dissimilar welded joint with diffusion interlayers test: AE data recorded under tension (**a**) and strain distributions over the painted area on different stages of test (**b–d**). Figure 9: Distribution of AE hits amplitudes for defect-free dissimilar weld specimen (**a**), and for a specimen with a confirmed presence of diffusion interlayers (**b**). The variation of amplitude values also significantly increases; for a defect-free specimen of a dissimilar welded joint, the standard deviation of the amplitudes distribution is about 28 dB, and for a specimen containing diffusion interlayers, the standard deviation value increases to 42 dB, probably due to the fact that, against the background of the main process (deformation of the specimen with a dissimilar welded joint), an additional process of the destruction of a brittle carbide interlayer takes place.
# Damping and Natural Period Evaluation of Tall RC Buildings Using Full-Scale Data in Korea
## 3 Empirical Formulae for Damping Ratio of RC Buildings for Wind Design
### Single-Value Damping Ratio
#### 3.1.2 The Australia and New Zealand Standard (AS/NZS 1170)  
AS/NZS 1170, which is used in Australia and New Zealand, uses the damping ratio of a building, regardless of building height and response amplitude. The damping ratio provided in AS/NZS 1170 depends on the serviceability limit state and the ultimate limit state for different types of structures. In terms of the serviceability limit state, structures are categorized into two types: steel structures and RC structures. In terms of the ultimate limit state, structures are categorized into three types: RC structures, bolted steel structures, and welded steel structures.  
The damping ratios provided in AS/NZS 1170 are presented In Table 3, along with those for the ultimate limit state for reference. The table shows that damping ratios for RC structures and steel structures are in the same range in terms of the serviceability limit state.
## 1 Introduction
The researchers identified slight differences in the resistance and stiffness, with a 10% to 20% difference in the stiffness. [PERSON] et al. [8] conducted numerical analyses that were validated with experimental work, and a comparison was made with other work, such as that mentioned above [15]. The numerical models were developed based on finite element models in _Abaqus software version 6.7_, utilizing eight-node linear hexahedral finite elements with reduced integration to model the specimen undergoing double-shear tests. The results of the numerical modeling demonstrated that the discrepancy in outcomes between the various test configurations is comparable in terms of stiffness, with a value of less than 2%. The study concluded that symmetrical shear tests resulted in lower stiffness than asymmetrical shear tests and higher stiffness than pure shear tests. [PERSON] et al. [16] investigated a TCC system with inclined screws and an interposed interlayer using a numerical finite element (FE) model implemented in Abaqus software and calibrated through tests. Interlayers with varied thicknesses and contact interactions were studied. It was concluded that between frictionless and bonded configurations (numerical study), the strength and stiffness could increase up to around 80%. The type of interlayer and the mechanical capacity are important parameters, as they affect the stiffness of the timber-concrete composite connection. In November 2021, the European Technical Specification CEN/TS 19103 [17] was published, providing general rules and rules for building design for timber-concrete composite structures as well as guidance on specimen configuration and shear test design.
# Review of Image Forensic Techniques Based on Deep Learning
## 2 Image Forensic Techniques
### Active Forensics
#### 2.2.3 Attacks of Robust Watermarking  
In the end-to-end watermarking framework, the attack simulation layer plays a decisive role in improving the robustness of the framework. However, when implementing backpropagation updates in parameters, it is necessary to ensure that each node is differentiable. For non-differentiable attacks, the model cannot perform parameter updates during backpropagation. Therefore, here comes a subdivision of whether the attack is differentiable or not.  
**Differentiable Attacks:**  
Noise and Filtering Attacks: Noise and filtering attacks refer to some intentional or unintentional attacks on the watermarked image in the electronic channel transmission, such as Gaussian noise, salt and pepper noise, Gaussian filtering, and median filtering. Its robustness can usually be improved by generating adversarial samples in the ASL layer.  
Geometric Attacks: Applying geometric attacks to an image can break the synchronization between the watermark decoder and the watermarked image. Geometric attacks can be subdivided into rotation, scaling, translation, cropping, etc.  
**Non-differentiable Attacks:**  
Joint Photographic Experts Group (JPEG) Attacks: The JPEG standard has two basic compression methods: the DCT-based method and the lossless compression prediction method. In this survey, we focus on the DCT-based JPEG compression, which can consist of DCT, inverse DCT, quantization, inverse quantization, entropy coding, and entropy decoding (i.e., color conversion and sampling), as shown in Figure 4. Quantization and dequantization are non-differentiable processes, leading to the incompatibility of the model with simulated attacks.  
Screen-shooting Attacks: In the process of watermarked images through the camera photo processing, it will undergo a series of analog-digital (A/D) conversion and digital-analog (D/A) conversion inevitably, both of which affect the extraction of the watermark seriously.  
Agnostic Attacks: Agnostic attacks refer to attacks in which the model parameters are unknown to the attack's prior information. For neural network models, it is difficult for the encoder and decoder to adapt to agnostic attacks without generating attack prior samples.
###### Abstract  
Development of a geotechnical database for the young capital of Kazakhstan, Nur-Sultan city, became a paramount concern of both the scientific community and industry. The creation of the Kazakhstan model of the geotechnical database was based on a fixed dataset which included a city map with determined X, Y, and H coordinates and the user generated data obtained from the materials of engineering and geological surveys from more than 2000 boreholes. Based on the assessment of the built-up area of the city, six main engineering-geological elements (EGE) were identified. The territory of the city was regrouped into eight zones instead of the previous six based on the geological origin and stratigraphy interposition of the EGE. Engineering properties of the soils were considered for physical and mechanical characteristics, where the plasticity limits demonstrated an accurate correlation to the elasticity modulus E and distribution boundaries between the alluvial and eluvial types of the soil on the graph. So, the increased liquid and plastic limits are replicated by higher values of elasticity modulus E, and hence better strength characteristics of a particular soil layer and vice versa, while the moisture content and soil density did not show any obvious pattern and requires additional verification on the construction site. Finally, a geotechnical map was built for the driven piles and the optimal variations in the pile length for each zone were determined.  
geotechnical mapping; geotechnical database; zoning; pile length optimization; driven piles 2021  
11
## 4 Precise Point Positioning Results
### CNES Evaluation
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c c} \hline \hline  & & \multicolumn{4}{c}{**Post-Processed Products**} & \multicolumn{4}{c}{**Real-Time Products**} \\  & & \multicolumn{2}{c}{**PPP-AR**} & \multicolumn{2}{c}{**PPP-Snapshot**} & \multicolumn{4}{c}{**PPP-AR**} & \multicolumn{4}{c}{**PPP-Snapshot**} \\ \cline{3-14}  & & **EWL** & **WL** & **NL** & **EWL** & **WL** & **NL** & **EWL** & **WL** & **NL** & **EWL** & **WL** & **NL** \\ \hline \multirow{2}{*}{1 Hz} & C/P [\%] & 40.28 & 35.12 & 18.04 & 47.89 & 16.71 & 16.95 & 38.08 & 33.76 & 16.39 & 36.96 & 16.65 & 16.90 \\  & C/P/D [\%] & 41.58 & 36.05 & 18.53 & 47.89 & 16.71 & 16.95 & 38.09 & 33.98 & 16.39 & 37.02 & 16.65 & 16.90 \\ \hline \multirow{2}{*}{10 Hz} & C/P [\%] & 48.42 & 44.93 & 35.78 & 49.38 & 17.22 & 17.47 & 40.36 & 38.37 & 24.85 & 38.71 & 17.29 & 17.53 \\  & C/P/D [\%] & 49.10 & 45.88 & 30.96 & 49.37 & 17.22 & 17.47 & 40.44 & 39.01 & 22.86 & 38.71 & 17.29 & 17.53 \\ \hline \hline \end{tabular}
\end{table} 
Table 10: Extra-widelane (EWL), widelane (WL), and narrowlane (NL) ambiguities fixing rates (in %) for the kinematic trajectory estimation in Toulouse, France, in several cases, at 1 Hz or 10 Hz, with code and carrier-phase measures only (C/P) or code, carrier-phase, and Doppler shift measures (C/P/D), with the real-time or the post-processed products. \begin{table}
\begin{tabular}{c c c c c c c c c c c c c c} \hline \hline \multicolumn{1}{c}{} & \multicolumn{8}{c}{**Position Results**} \\ \hline  & & \multicolumn{4}{c}{**Post-Processed Products**} & \multicolumn{4}{c}{**Real-Time Products**} \\  & & \multicolumn{2}{c}{**PPP-AR**} & \multicolumn{4}{c}{**PPP-Snapshot**} & \multicolumn{4}{c}{**PPP-AR**} & \multicolumn{4}{c}{**PPP-Snapshot**} \\ \cline{3-14}  & & **mean** & **std. ** & **95\%** & **mean** & **std. ** & **95\%** & **mean** & **std. ** & **95\%** & **mean** & **std. ** & **95\%** \\ \hline \multirow{2}{*}{1 Hz} & C/P [m] & 1.51 & 2.25 & 5.95 & 1.59 & 2.36
## 3 Calculation Methodology of the PVCS Carbon Impact
### Presentation of the Study Perimeter
#### 3.2.1 Carbon Impact of the PV System
The maintenance carbon impact of the PV system is calculated according to the following equation:  
\[Imp_{maint}=Imp_{cleaning}+Imp_{agt\,transport}=CO_{2,cleaning} \cdot A_{PV}+CO_{2,agt\,transport}\cdot d\cdot q \tag{29}\]  
where \(Imp_{cleaning}\) and \(Imp_{agt\,transport}\) are the carbon impacts of PV cleaning and transporting maintenance agents to the PV system in kgCO2,eq, respectively, \(CO_{2,cleaning}\) is the carbon emission coefficient for cleaning PV panels in kgCO2,eq/m2, \(CO_{2,agt\,transport}\) is the carbon emission coefficient of transporting maintenance agents to the PV system in kgCO2,eq/km, \(A_{PV}\) is the area of PV panels in m2, \(d\) is the annual distance traveled by maintenance agents in km/year, and \(q\) is the lifespan of PV panels in years.
# A Study on Sensitive Bands of EEG Data under Different Mental Workloads
## 5 Conclusions  
In this paper, the sensitive bands of EEG data under different mental workloads are studied. The signals are obtained through different flight load experiments. Feature extraction is performed by calculating the PSD and energy of the EEG signal. According to the feature selection of Gini impurity, the importance index of different bands of EEG data is analyzed using the Gini index, and the  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Subject Number** & **Acc(\(f\))** & **Acc(\(\beta\))** & **Acc(\(\beta\)) – Acc(\(f\))** \\ \hline Subject 01 & 72 & 73 & +1 \\ Subject 02 & 72 & 74 & +2 \\ Subject 05 & 87 & 86 & \(-1\) \\ Subject 06 & 90 & 93 & +3 \\ Subject 07 & 89 & 91 & +2 \\ Subject 08 & 77 & 77 & 0 \\ Subject 10 & 79 & 81 & +2 \\ Subject 12 & 96 & 96 & 0 \\ Subject 18 & 91 & 92 & +1 \\ Subject 22 & 87 & 89 & +2 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Classification accuracy of the four band features and the \(\beta\) band feature on the test set (unit: %).  
Figure 13: Classification confusion matrix using \(\beta\) band data alone.  
characteristics of the band with higher importance are obtained. It is found that the \(\beta\) band has the highest importance and sensitivity under different mental loads. The data of the four bands and the data of the separate \(\beta\) band are sent to the SVM classifier for verification. By observing the final classification accuracy, it is found that the data of the \(\beta\) band alone has higher final classification accuracy than the data of the four bands. This also shows that the \(\beta\) band data is more important and sensitive than other bands under different brain loads, and can represent the entire EEG data for subsequent data analysis.  
The manuscript was written through contributions of all authors. Conceptualization, H.Q. and Z.F.; data curation, Z.F. and J.Z.; formal analysis, H.Q. and S.C.; funding acquisition, L.P. and S.C.; investigation, Z.F. and H.Q.; methodology, H.Q. and S.C.; project administration, H.Q. and L.P.; resources, H.W.; software, Z.F. and J.Z.; supervision, H.Q.; validation, Z.F.; visualization, Z.F. and L.P.; writing-review-editing, H.Q., Z.F., and H.W.  
This research was funded by Liao Ning Revitalization Talents Program, grant number XLYC1802092.  
The authors would like to thank [PERSON], [PERSON], and [PERSON] for conducting the experimenters in the laboratory and for their great contribution in data-collection work.  
The authors declare no conflict of interest.
## 5 Conclusions  
A fractional order sliding mode control (FOSMC) was proposed for the trajectory tracking control for an integer second order nonlinear system with an unknown perturbation term. A sufficient condition was given to assure the attraction of the sliding surface where trajectory tracking is achieved. The sufficient condition found allows to adjust two parameters (\(\sigma_{\chi}\) and \(\mu_{\chi}\)) of the FOSMC in order to assure the attraction to the sliding surface proposed. Besides, an application of the methodology to the trajectory tracking of a quadrotor dynamical model is given. Simulation results were obtained for a given trajectory, including take-off and landing. These results were also compared with an IOSMC showing that chattering can be diminished in some of the control signals, when using FOSMC, and in the presence of additive perturbations. The results obtained are promising and further research is being carried out together with experimentation with a real quadrotor.  
The contribution of each author is as follows: conceptualization R.C.-L. and M.A.D.-M.; formal analysis R.C.-L. and M.A.D.-M.; methodology R.C.-L.; project administration M.A.D.-M.; software N.A.-C. and A.G.-V.; supervision M.A.D.-M. and N.A.-C.;validation N.A.-C.; visualization A.G.-V. and G.E.C.-B.; writing original draft A.G.-V.; writing review and editing G.E.C.-B.  
This research received no external funding.  
The authors would like to thank Consejo Nacional de Ciencia y Tecnologia CONACYT, Mexico, under grant 786275 and grant CB-2019-01,254329.  
The authors declare no conflict of interest.  
Figure 33: Yaw Torque \(u_{4}\).  
Figure 32: Pitch Torque \(u_{3}\).
# Modeling of Dry Clutch Wear for a Wide Range of Operating Parameters
## 6 Wear Rate Expectation Model
### Comparison with Baseline Model  
To further illustrate the developed wear rate model accuracy and applicability, the model performance metrics are compared with the metrics of the common, baseline model having only temperature as the single, most influential input parameter. The results presented in Table 5 indicates that the standard deviation of residuals of proposed model is reduced by around 60% when compared to that of the baseline model for the modeling dataset, while the R\({}^{2}\) index is increased from 0.583 to 0.875. The performance metrics are also considerably improved when considering the validation dataset if the outlier-like Point 13 is excluded from the dataset.
## 7 Comparison with Related Works and Served Applications  
The proposed antenna results are compared with the related works available in the literature for different aspects and the comparisons are tabulated in Table 6. The proposed antenna has a relatively smaller size and can pass low frequencies due to the meander arm structure. Additionally, the proposed antenna can operate at seven distinguished bands by satisfying the UWB license range. The maximum gain is acceptable for such a monopole antenna, and it is lower than some works in the literature due to the multiband mode of operations.