esa-sceva/satcom-chunk-collection huggingface dataset:
# Intelligent Design of Pavement Concrete Based on RSM-NSGA-III-CRITIC-VIKOR
## 2 Materials and Methods
### Mix Design
#### 2.3.1 Selection of Independent Variables  
W/C ranged from 0.35 to 0.43, carefully determined based on code recommendations and the target flexural strength requirements. This parameter was selected as a primary variable due to its fundamental role in controlling the hydration reaction kinetics and resultant pore structure of the cement paste, directly influencing both strength development and long-term durability of the concrete. As demonstrated by [PERSON] [6], the optimization of W/C is critical for concrete pavements in extreme environments with large daily temperature differences, where inappropriate W/C selection can lead to significant performance degradation and premature failure. [PERSON] [37] further confirmed that W/C significantly impacts concrete's susceptibility to plastic shrinkage cracking in arid conditions characterized by high temperatures and wind speeds--conditions analogous to the Gobi Desert environment. Lower W/C values (0.35) provide enhanced strength and reduced permeability, while higher values (0.43) improve workability but potentially compromise durability in severe exposure conditions.  
The sand ratio was established between 36% and 42%, a range meticulously optimized through extensive slump testing to ensure a target slump of 50 mm, thus achieving an optimal balance between mechanical performance and workability. [PERSON] and [PERSON] [38] demonstrated that aggregate proportioning significantly affects not only the mechanical properties but also the permeability and durability characteristics of concrete pavements. The lower boundary (36%) ensures adequate coarse aggregate content for structural integrity, while the upper boundary (42%) prevents excessive sand content that could lead to workability issues and increased shrinkage potential.  
AEA dosage ranged from 0.1% to 0.3% by mass of cement, validated through systematic air content testing. This variable was selected due to its critical role in creating a controlled network of microscopic air bubbles that significantly improves freeze-thaw resistance and reduces internal stresses caused by thermal variations. [PERSON] [39] confirmed that proper air void distribution is essential for enhancing pavement durability in severe environmental conditions. Our experimental validation demonstrated that this dosage range successfully maintained air content within 5 \(\pm\) 0.5%, optimizing the balance between strength and durability. The introduction of uniformly distributed microbubbles significantly improved pore size distribution and reduced shrinkage potential through stress redistribution mechanisms.  
Additionally, a water-reducing agent dosage was fixed at 0.6% of the cement mass, optimized through multiple trial mixes to ensure consistent flowability and mixture uniformity without affecting the primary variables under investigation.
## 2 Fundamentals of Terahertz Communication
### Advantages of THz in FSO Systems  
Several aspects of using THz frequencies make them suitable for free-space optical communication systems, especially for next-generation applications. A significant advantage is the additional bandwidth provided by the THz range. Bandwidths in the THz range can hold data transfer rates of over 1 Tbps, which is far more than those of the microwave or optical communication systems [46]. This places THz communication in a very suitable place for use in data-hungry scenarios like 6G networks, HD streaming, and real-time analysis. Reports have shown that THz-based links support a data transmission capacity up to 4 Tbps for a short range [47].  
Another equally important advantage is miniaturization, which is made possible by the fact that the THz frequency is shorter in wavelength. The range between 30 \(\upmu\)m and 3 mm produces the possibility of developing compact antennas and fabricating elements that are suitable for integration into portable systems or on-chip [48]. Miniaturization lowers the general form factor of communication gear, making THz systems appealing for use in satellite communication equipment, UAV platforms, and wearable devices. The future development of nanofabrication could improve these compact designs further so that their energy utilization is efficient and their performance is equal to that of existing systems [18; 49].  
Specifically, the THz spectrum is also advantageous in terms of minimizing interference with currently running systems of communication [19; 50; 51]. Thanks to its low-frequency repetition rate, the THz band is not confused with the densely populated microwave and optical ranges and, therefore, has less signaling interference. This characteristic is extremely desirable in densely populated areas where signal interference is likely to affect the system's operation. In addition, the implementation of THz signals with a narrow beamwidth improves the physical layer security by minimizing the chances of interception or eavesdropping [52; 53].
## 4 Proposal
### Text Extraction Function  
The _text extraction function_ pre-processes the _isolated sign image_ before retrieving and cleaning the text from the image. The OpenCV implements the pre-processing step to standardize the image quality [47]. Then, _PaddleOCR_ recognizes and extracts text from pre-processed images. Finally, the extracted text is cleaned of uppercase letters and punctuation using the _regular expression (re)_ library [48].  
Figure 4: Example input image with sign.  
First, we employ image normalization and contrast enhancement through OpenCV to standardize the image quality, addressing the varied illumination levels in the surrounding environment. This includes noise reduction through blur functions, bilateral filters, and average brightness adjustment through histogram equalization.  
Then, due to its high accuracy in various illumination conditions, as reported in [49], we utilize _PaddleOCR_ to automatically recognize and extract text from the standardized _isolated sign image_. This detects text in images, adjusts the orientation of the detected text to horizontal, and recognizes text from the corrected orientation.  
Finally, the system removes lowercase letters and punctuation that might be generated from the output of the _PaddleOCR_ using the _re_ library. This step produces cleaned text that is ready to be compared with the room number in the room database for the _database matching function_.
## 3 Numerical Model
### Model Verification  
From the perspective of crack development characteristics, the constitutive model of the numerical model and the rationality, accuracy of the mechanical parameters is verified. As shown in Figure 11, the completeness of the surrounding rock at 2 m, 5 m, and 8 m is observed via a borehole television (TV). It can be see that at 2 m, a large number of cracks are generated in the coal body, and the cracks penetrate each other to form a fracture zone. With the depth increase to 5 m, the amount of the cracks reduced, but the fracture zone can still be observed. However, for coal mass at depth of 8 m, only a small amount of cracks can be seen, and the coal mass almost remains intact. In the corresponding position, the crack development in the numerical simulation is basically consistent with the borehole  
Figure 10: Numerical model.  
TV observation, which verifies the reliability and accuracy of the simulation from the perspective of surrounding rock failure.
# Analysis of the Influence of Segmented Rollers on Slab Bulge Deformation
## 5 Influences of Roller Spacing and Roller Diameter on Slab Bulge Deformation  
### Establishment of Deformation Model with Different Roller Spacings and Diameters  
In the continuous casting process, bulge deformation must be controlled to ensure the quality of the slab. There are many factors involved in slab bulge deformation in continuous casting production, among which the main parameters include casting speed, static pressure of molten steel, shell thickness, roller spacing, roller diameter, and surface temperature of the slab. The main purpose of this section is to explore and analyze the influence of the segmented roller structure parameters on bulge deformation. Under a constant casting speed condition (1.5 m\(\cdot\)min\({}^{-1}\)), the bulge deformation was calculated and analyzed for the casting slab. The specific simulation structural parameters are shown in Table 5. The influence of the casting process parameters was numerically analyzed by a comparison between the average values of the bulge deformation.
## 1 Introduction
The dynamic behavior of a wind energy conversion system also depends on the moment when the electric generator is connected to the grid: either from the beginning [2; 29; 35; 45] or at a time after start-up [36; 41]. [PERSON] et al. [36] stated that synchronous or DC motors can be operated as induction generators if their shaft rotation speed overcomes the synchronous speed. However, this study did not address the optimization problem or the impact of the generator connecting time to the grid on the system's dynamic behavior. Based on this literature review, the following gaps emerge:  
* Choosing an appropriate model of the mechanical characteristics specific to the operating condition of the wind system is still a challenging issue;
* The rotation of the satellite gears from planetary speed increasers is typically neglected;
* The choice of the optimal time for connecting the electric generator to the grid. Aiming at dealing with these gaps and deepening the understanding of the optimal functioning of a wind system, the present study brings contributions and focuses mainly on the following aspects:  
1. The dynamic modeling is carried out analytically by applying the Newton-Euler method and the MATLAB-Simulink R2014a software in numerical simulations;
2. The functional compatibility of the wind system is ensured by the planetary speed increase, whose input is connected to the wind rotor, and its two outputs are connected to the generator rotor and stator, respectively;
3. The satellite's own rotation was considered in dynamic modeling by using an equivalent axial moment of inertia;
4. The mechanical moments of inertia of the transmission components were reduced at the shafts of the wind rotor and the electric generator;
5. The nonlinear mechanical characteristic of the wind rotor is linearized on four zones;
6. The dynamic system response is given by a simulation module that allows the generator to connect to the grid after the wind rotor enters the maximum power zone. This simulator also allows the identification of the dynamic behavior of the considered subsystems through specific parameters such as power, torque, speed, and efficiency. Based on the actual reported results, to the best of our knowledge, the dynamic behavior of this type of wind system with a counter-rotating generator and planetary speed increase has not been significantly addressed in the literature. Aiming to cover this literature gap, the paper proposes a generalized algorithm for close-form dynamic modeling of single-rotor wind turbine class with planetary speed increase and counter-rotating generator, patented by authors [46]. The subsequent sections of the paper are organized as follows: Section 2 introduces the conceptual and block diagrams of a counter-rotating wind turbine and formulates the dynamic modeling problem. Section 3 details the proposed generalized algorithm for analytical dynamic modeling. Numerical results for a 100 kW wind turbine are presented and discussed in Section 4, and the paper concludes in Section 5.
## 2 Materials and Method
### Datasets  
#### 2.2.1 Rain Gauge Data  
The daily precipitation dataset from 387 stations, between March 2014 and December 2016, were obtained from DHM Nepal ([[https://www.dhm.gov.np/contents/resources](https://www.dhm.gov.np/contents/resources)]([https://www.dhm.gov.np/contents/resources](https://www.dhm.gov.np/contents/resources))). The DHM stations provide daily datasets at 03 UTC. For the consistent measurement, DHM uses the same type of the United States standard eight-inch diameter manual rain gauges [53]. In addition to DHM datasets, data from a high-elevation Automatic Weather Station (AWS) located in the Everest region (27.95\({}^{\circ}\)N to 86.20\({}^{\circ}\)E, 5050 masl), Pyramid was also used.  
In total, 388 stations' data were used for evaluation of SBP products (Figure 1), which were further subjected to quality control. The remote location, unavailability of AWS, lack of regular monitoring and maintenance of rain-gauge stations are the primary causes for discontinuities in the data series. Data coverage (%) at each station between March 2014 and December 2016 is presented in the Supplementary Materials (S1). The observations from 125 gauges were used in the development of the Global Precipitation Climatology Centre (GPCC) product, which was, in turn, used to calibrate IMERG precipitation totals [55]. About 54 stations also belonged to the Global Telecommunications System (GTS) and were used for the National Oceanic and Atmospheric Administration (NOAA)/CPC analysis, which was in turn used to calibrate the daily GSMaP-Gauge product [56]. Therefore, there is a potential dependency problem between the gauge observed and gauge-corrected SBP product used in this study. The mean precipitation (mm/day) at each rain-gauge station during the study period is presented in Figure 3a.
## 4 Experimental Validation and Discussion
### Discussion of Excitation Amplitude on Vibration Characteristics  
In order to verify the influence of the excitation amplitude on the performance of the piezoelectric energy harvester, the excitation frequency is set to 11 Hz, and the response  
Figure 17: Simulation results of time-domain velocity versus the displacement when \(A=14\) m/s\({}^{2}\): (a) \(f=6\) Hz; (b) \(f=9\) Hz; (c) \(f=12\) Hz.  
Figure 18: Voltage–time diagram when \(A=14\) m/s\({}^{2}\): (a) \(f=6\) Hz; (b) \(f=9\) Hz; (c) \(f=12\) Hz.  
and output characteristics of the piezoelectric energy harvester were measured under the conditions of \(A=8\) m/s\({}^{2}\), \(A=11\) m/s\({}^{2}\), and \(A=14\) m/s\({}^{2}\).  
Figure 19a-c shows the simulation results of time-domain velocity versus the displacement when \(f=11\) Hz and the excitation amplitude is 8 m/s\({}^{2}\), 11 m/s\({}^{2}\), and 14 m/s\({}^{2}\), respectively. Figure 20a-c shows the voltage-time diagrams when \(f=11\) Hz and the excitation amplitude is 8 m/s\({}^{2}\), 11 m/s\({}^{2}\), and 14 m/s\({}^{2}\), respectively. Under the excitation conditions of \(A=8\) m/s\({}^{2}\) and \(A=11\) m/s\({}^{2}\), the RMS voltages produced by BPEH are 2.03 V and 3.22 V, while IBPEH is 10.47 V and 25.29 V, respectively. The RMS voltage of the yield of the IBPEH is 5.15 times and 6.85 times that of the RMS voltage of the output of the BPEH in turn. When the excitation amplitude is 14 m/s\({}^{2}\), the RMS voltages of the BPEH and IBPEH are 19.77 V and 26.37 V, respectively, and the output of IBPEH is 33.38% higher than that of BPEH. Compared with the simulation results, when the excitation frequency is 11 Hz and the excitation amplitude is 8m/s\({}^{2}\), although the IBPEH shows a chaotic motion state in both the simulation and the experiment, the RMS voltage output in the experiment is low, which is why there are more small-amplitude intrawell motions in the experiment, resulting in a less high-energy output of IBPEH. The experimental results show that the response output characteristics of IBPEH are always higher than those of BPEH under different excitation amplitudes, and that IBPEH can achieve sustained high-energy output at lower excitation amplitude.
## 2 Materials and Methods
The expansion of the torque expression in a Taylor series with the trigonometric terms considered up to the fifth order gives the following expression for the quintic (essentially) nonlinear stiffness function:  
\[I_{G}\ddot{\theta}_{G}-R_{p}C_{M}\dot{x}_{t}-R_{G}K_{M}x_{t}+K_{N}(\theta_{G}- \theta_{N})^{3}+C_{N}\Big{(}\dot{\theta}_{G}-\dot{\theta}_{N}\Big{)}=-T_{G}, \tag{2}\]1  
with \(k_{3}=\frac{192\,l^{2}E\,I}{l^{3}}\), \(k_{5}=\frac{48 Elh^{2}\left(48l^{2}-l^{2}\,\right)}{l^{3}}\). Previous modelling work that was briefly described in Section 2 has considered purely cubic stiffness; however, practical realisations that would eliminate the quintic term were found hard to implement. Therefore, the quintic term was retained in the nonlinear NES torque design, aiming for the torque given by Equation (6) to approach the theoretical \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline Modulus of elasticity (\(E\)) & \(2\times 10^{11}\) N/m\({}^{2}\) \\ Shim thickness (t) & 0.0012 m \\ Shim width (w) & 0.012 m \\ Shim length (L) & 0.076 m \\ Half-length of the rocker arm (h) & 0.047 m \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Material and geometrical properties of the NES shims. Figure 5: (**a**) Unloaded and (**b**) loaded snapshots of the NES shims. cubic torque as much as feasible. Using the values in Table 1, the stiffness coefficients are calculated as \(k_{3}=334\) Nm/rad\({}^{3}\) and \(k_{5}=1449\) Nm/rad\({}^{5}\). Figure 6 shows a comparison of the theoretical target torque with the designed torque given by Equation (5) and with its Taylor expansion given by Equation (6). The quintic expansion shows excellent agreement with the designed torque for the examined angle range, which makes it reasonable to drop terms of higher order. Furthermore, a small deviation from the originally targeted torque profile is observed, which, nevertheless, is too small to cause any concern regarding the effect of the NES on the gear amplitude. In order to establish robust TET conditions between the NES and the primary (host) system, the NES damping content has to be as low as possible so that it does not contaminate the essentially nonlinear force. Thus, the friction between the dowel and roller surfaces should be low to favour pure rolling motion. To achieve this, the NES roller assembly should be lubricated. A roller bearing with a low friction coefficient is an attractive alternative and it has been employed in this work. This bearing type can exhibit a static coefficient of friction between 0.002 and 0.005, whereas the kinetic friction coefficient can vary between 0.001 and 0.0018.
## 2 State-of-the-Art
### Reputation Systems
In the WorkerRep system [49], task completion involves evaluators scoring submissions based on two criteria: completeness and quality. These scores are then weighted according to the credibility of the evaluators, which is determined by their own reputation on the platform. Outlier scores are excluded, and a consensus score is calculated from the remaining evaluations. Workers who participate in evaluating peers also have their reputations updated based on the accuracy of their evaluations relative to the consensus. There is also a rewards system that takes reputation into account. RepChain [50] uses a consortium blockchain (CBC) to enable e-commerce platforms to collaboratively maintain a decentralized ledger. It incorporates one-show anonymous credentials, created with two-move blind signatures, to protect customer identities and prevent multiple rating abuses. Zero-knowledge range proofs are used to verify the accuracy of ratings, protecting against abnormal rating attacks. Reputations are updatedusing secure multiparty computation. Additionally, consensus hashing is used to verify ratings through batch processing and consensus hashes. The authors in [51] propose a reputation system that incorporates a trust value, a distrust value, and an uncertainty value that adds up to 1. The trust value represents the level of trust that node i has towards node j. It is a measure of positive interactions and indicates the probability that node j will perform as expected. The higher the trust value, the more confidence node i has in node j's reliability. The distrust value shows the level of distrust node i has toward node j. A higher distrust value indicates greater suspicion that node j won't meet expectations. The uncertainty value captures the level of uncertainty in the opinion of node i regarding node j. It accounts for the lack of sufficient interaction history or contradictory information, representing the extent to which node i is unsure about node j's trustworthiness. A higher uncertainty value means that node i has less information or is less certain about the performance of node j. The reputation calculation includes the timeliness of interactions and the property of interactions. For example, the timeliness function applies a decay factor to older interactions to give more weight to recent activities. Positive and negative interactions are treated differently, with negative interactions leading to a more rapid decline in reputation.
## 2 Method
### CNN-Transformer Hybrid Model Based on IBKA  
In order to achieve accurate predictions of weir dam life, a CNN-Transformer hybrid model based on the Improved Black-Winged Kite Optimization Algorithm (IBKA) is suggested in this study. The method combines the quantitative features of weir dams (e.g., dam height, dam width, and dam volume) and qualitative features (e.g., triggering factors and material types) to fully utilize the complementary advantages of the two types of features. The model uses CNN to extract local patterns from quantitative features and discovers intrinsic geometric patterns through convolution and pooling operations; subsequently, the Transformer module further captures the global feature interactions through the multi-head self-attention mechanism, especially the combined effects of triggering factors and material types on the lifespan.  
The Improved Black-Winged Kite Algorithm (IBKA) is utilized to optimize key hyperparameters in the CNN-Transformer hybrid model, ensuring enhanced convergence efficiency and predictive performance. Specifically, IBKA fine-tunes the convolutional kernel size in the CNN component, which significantly impacts the model's ability to extract local features. A larger kernel captures broader patterns, whereas a smaller kernel enables fine-grained feature extraction, and IBKA dynamically balances this trade-off to improve feature representation while maintaining computational efficiency. Additionally, IBKA optimizes the number of Transformer layers, a critical factor in capturing long-range dependencies and complex global interactions. While increasing the number of layers enhances the model's capacity for learning intricate relationships, excessive layers may lead to overfitting or prolonged training time; thus, IBKA ensures an optimal depth that maximizes learning efficiency without compromising generalization. Furthermore, IBKA fine-tunes the number of attention heads, which determines the degree of parallelization in the Transformer's multi-head attention mechanism. More attention heads enable the model to capture diverse feature relationships, particularly in high-dimensional data, but an excessive number may increase computational cost and reduce training efficiency. By systematically optimizing these hyperparameters, IBKA accelerates model convergence, improves predictive accuracy, and enhances the generalization capabilityof the CNN-Transformer hybrid model, allowing it to effectively capture both local and global dependencies in landslide dam lifespan prediction.  
Finally, the optimized model is used for training, based on the mean square error (MSE) as the objective function, and the prediction accuracy is evaluated using the test set. The method provides an efficient and reliable solution for weir life prediction by combining the local and global feature modeling capabilities, and at the same time, demonstrates strong practicality and robustness in handling mixed feature data. The framework diagram of the intelligent prediction model used to predict weir life is shown in Figure 3.