esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Results and Discussion
### Verification of Numerical Simulation
#### 4.1.2 Numerical Modeling Procedure  
In the modeling process of this study, to simplify the analysis, seepage effects were not considered. This is mainly because a bottom-sealing waterproof curtain was employed, which extends into the weak permeable layer to isolate the water connection between the interior and exterior of the excavation pit, allowing for \"dry\" excavation. It was generally assumed that dewatering within the excavation had little impact on the water level outside the excavation. Therefore, the difference in water levels between the inside and outside of the excavation could be directly defined [2]. The pore pressure distribution on both sides of the retaining structure was then calculated using the hydrostatic pressure method, with the \"phreatic surface\" type selected for the pore pressure calculation. Accordingly, it was assumed that the pore water pressure above the groundwater table was zero, and the interface elements of the retaining piles were set as impermeable. The water head within the pit was set at 0.5 m below the excavation surface, and the hydrostatic pressure was calculated.  
According to the construction process provided by the chosen scheme, the excavation process of the foundation pit was simulated as follows:  
1. Calculation of the initial in situ stress field.
2. Generation of the tunnel structure.
3. Generation of the retaining and isolation piles.
4. Excavation to 2.9 m below ground level.  
\begin{table}
\begin{tabular}{c c c c} \hline
**Structure** & **Element Type** & **Elastic Modulus (MPa)** & **Poisson Ratio** \\ \hline
1 st strut & Beam & 30.0 & 0.2 \\
2 nd strut & Beam & 30.0 & 0.2 \\ Tunnel & Plate & 34.5 & 0.2 \\ Retaining pile & Plate & 30.0 & 0.2 \\ Isolation pile & Embedded beam & 30.0 & 0.2 \\ \hline \end{tabular}
\end{table}
Table 3: The main structural model parameters.  
Setting of the first-level horizontal struts.  
Excavation to 7.6 m below ground level.  
Setting of the second-level horizontal struts.  
Excavation to the bottom of the pit.  
A meshing sensitivity analysis was conducted to ensure the accuracy of the results. Specifically, when the number of elements was increased by 100%, the change in the maximum tunnel deformation was less than 3%. This indicates that the mesh used was adequately refined.
# Joint AP Association and Bandwidth Allocation Optimization Algorithm in High-Dense WLANs
## 3 Network Model and Design Requirements
### Motivation  
Performance anomaly refers to the effect that, when different rate clients associating with an AP, the throughput of the high rate clients will be degraded by the low rate clients [18], thus resulting in the decline of the system aggregated throughput. Here, a specific example is provided to demonstrate the throughput loss caused by performance anomaly. Consider a WLAN with 2 APs (AP1 and AP2) and 4 STAs, enumerated from 1 to 4, as depicted in Figure 1[19]. STA1 and STA2 experience a bit rate of 11 Mbps from AP1, while STA4 also experiences a bit rate of 11 Mbps from AP2. STA3 is the newly arriving one, which is in the overlapping area between AP1 and AP2. STA3 can associate with either AP1 or AP2. If it associates with AP1, STA3 will have a bit rate of 11 Mbps, and when all clients associating with AP1 have the same bit rate, AP1 will obtain distribute bandwidth without suffering performance anomaly. However, if it chooses AP2, it will have a bit rate of 1 Mbps, and when all STAs associating with AP2 have different bit rates, AP2 will suffer performance anomaly. The analysis from the experimental data in Table 1 demonstrates the performance anomaly that is a main factor to degrade system throughput [19].  
In Table 1, achievable throughputs are based on the analysis of [18], whereas those in parentheses are achieved by the simulation with OPNET. From the data of Table 1, it is noticed that though AP1 is more congested than AP2, if STA3 associates with AP1, the system throughput will be higher than that when it selects the counterpart AP2. Therefore, the bandwidth allocation scheme needs to be considered to eliminate the performance anomaly problem, preventing low rate clients from dominating the channel.  
Figure 1: Scenario illustrating performance anomaly [19].
# Short-Term Power Load Prediction of VMD-LSTM Based on ISSA Optimization
## 4 Performance Indicators  
In this study, four performance metrics are employed to evaluate the prediction accuracy of the proposed model: the root mean square error \(E_{RMSE}\), the mean absolute error \(E_{MAE}\), the mean absolute percentage error \(E_{MAPE}\), and the coefficient of determination \(R^{2}\). The mathematical definitions are given by  
\[E_{RMSE}=\sqrt{\frac{\sum_{t=1}^{N}(y_{t}-\hat{y}_{t})^{2}}{N}} \tag{27}\]  
\[E_{MAE}=\frac{\sum_{t=1}^{N}|y_{t}-\hat{y}_{t}|}{N} \tag{28}\]  
\[E_{MAPE}=\frac{\sum_{t=1}^{N}\frac{|y_{t}-\hat{y}_{t}|}{y_{t}}}{N}\times 100 \% \tag{29}\]  
\[R^{2}=1-\frac{\sum_{t=1}^{N}(y_{t}-\hat{y}_{t})^{2}}{\sum_{t=1}^{N}(y_{t}- \overline{y}_{t})^{2}} \tag{30}\]  
where \(N\) represents the number of samples, and \(y_{t}\), \(\hat{y}_{t}\), and \(\overline{y}_{t}\) denote the true value, predicted value, and average value of the data at time \(t\), respectively. For \(E_{RMSE}\), \(E_{MAE}\), and \(E_{MAPE}\), smaller values signify a higher prediction accuracy, and all these metrics fall within the range of \([0,1]\). A value of \(R^{2}\) closer to unity indicates that the fit is better.
## 3 Proposed SPMIPv6 Protocol  
### SPMIPv6 Protocol Architecture  
To introduce energy efficient mobility we propose Sensor Proxy Mobile IPv6 (SPMIPv6) for IP-WSN. It is a localized mobility management protocol based on PMIPv6. The SPMIPv6 architecture consists of a sensor network-based localized mobility anchor (SLMA), a sensor network-based mobile access gateway (SMAG) and many fully functional IPv6 header stack enabled IP sensor nodes. We discuss the individual module of the proposed architecture with the help of Figure 1.
## 1 Introduction
### Self-Healing Networks
#### 1.5.4 Statistical Methods  
Identifying the cause of faults in [30] was done by comparing the values of numerous indicators and taking appropriate corrective action, based on expert judgment. The opera tional approach involved ranking the causes of the set of indicators that strayed from their profile in decreasing relevancy. The scoring system employed in this approach determined the likelihood of a specific cause for an occurred fault, using the set of indicators that deviated from the baseline.  
In [31], the network status was examined using the characteristic vector of the network status, which was as long as the number of the analyzed indicators. This characteristic vector considered the threshold limit for the six most significant indications. The Hamming distance was used to determine how various records differed. As a result, the fault cause was the same for records that belonged to the same category. The expert specified the number of categories.  
A multilayer hierarchical structure was used in [32; 33] for fault-cause couples. The collection of current criteria was classified according to the knowledge of industry professionals. Counters were utilized in this study as an alternative for key performance indicators.
# Systemic Evaluation of PSS in the Early Concept Phase Using Graph-Based Reasoning
## 3 State of the Art
### Graph-Based Reasoning in the PSS Concept Phase
In this approach, specific drivers for the domain are elaborated, and a corresponding BN was modeled as a use case, not focusing on knowledge gaps and PSS concept assessment. [PERSON] et al. [60] examined various case studies of PSSs and used a BN to map the frequencies with which certain types of PSSs encounter implementation barriers as a probabilistic graph based on a dataset. Therefore, they did not capture the uncertain knowledge of PSS engineers in reasoning about performance levels of PSS concepts. [PERSON] [61] used a BN to visualize the most prominent relationships between product features and matching service components in a PSS based on a dataset. However, they used the BN framework for statistical data analysis and not for the modeling of uncertain domain knowledge. Many approaches use a BN as a statistical tool for data analysis, e.g., to identify relationships among PSS elements. They are not used to systematically anticipate the vague behavior of PSS concept variations with their associated knowledge gaps in understanding and resulting impact on evaluation metrics in a transparent and comprehensible way during the concept phase of PSSs. In conclusion, PSS concept evaluation approaches focus mainly on value models but suffer from uncertainty and a failure to identify most critical issueswithin a PSS concept to focus on improving the evaluation and performance levels. Engineering-centric approaches are either very domain-specific in their assessment and require a high level of modeling effort or often rely on existing data and deep domain understanding. Risk assessment methods for PSS concept evaluation, while specifically focusing on uncertainty and its effects, do not allow the effects of epistemic knowledge gaps within concept alternatives on assessment criteria to be attributed in a transparent and flexible way, as they fail to provide executable models that can depict the underlying causal reasoning. Bayesian networks are a suitable tool for this, already used in risk assessment. However, in the domain of PSS concept design and evaluation, the use of BNs has not been studied to assess PSS concept variations and the influence of respective knowledge gaps in a transparent way.
## 4 Experiments and Analysis
### Ablation Experiment  
In order to evaluate the performance of the PTKRE models, this section includes ablation experiments on the model. Based on the different pre-trained language models used, these ablation experiments are divided into two control groups: BERT-large and RoBERTa-large. In each ablation experiment group, there are three comparative models:  
1. PTKRE-Att model: Change the multi-head attention layer of the PTKRE model that fuses prompt information and Top-K prediction set to average pooling operation. Moreover, we removed the entity location prediction layer.
2. PTKRE-Pos model: We removed only the entity location prediction layer in the PTKRE model.
3. PTKRE-ChatGPT model: Maintain the basic structure of the PTKRE model and remove only the augmented data generated by ChatGPT in the training set.  
The results of two sets of ablation experiments using BERT and RoBERTa are shown in Tables 6 and 7. By observing the experimental results of the two control groups, the following conclusions can be drawn:  
1. PTKRE vs. PTKRE-Att: After the PTKRE-Att model changes the fusion method of prompt information and Top-K prediction set to average pooling, the model's F1 score decreases in both sets of experiments. It shows that the multi-head attention can more effectively fuse the \"<mask>\" token in the prompt information and the relationship representation in the Top-K prediction set.
2. PTKRE vs. PTKRE-Pos: After removing the entity location prediction layer from the PTKRE model, the F1 score of the model decreased by 0.14 in both sets of experiments. It shows that the entity position prediction task can effectively assist the model in determining the relative positions between entities in a sentence, thereby enhancing its performance in predicting the relationship categories between entities.
3. PTKRE vs. PTKRE-ChatGPT: After removing the augmented data generated by ChatGPT from the training set, the F1 score of the model decreased noticeably in both control experiments, with reductions of 0.19 and 0.2, respectively. These results indicate that data augmentation significantly impacts the performance of supervised relationship extraction models. The reason for this is that supervised model performance relies heavily on the goodness of the training set, which has high quality and a large amount of data that helps to improve the generalization of the model.
###### Abstract  
The accurate estimation of flood risk depends on, among other factors, a correct delineation of the floodable area and its associated hydrodynamic parameters. This characterization becomes fundamental in the flood hazard analyses that are carried out in urban areas. To achieve this objective, it is necessary to have a correct characterization of the topography, both inside the riverbed (bathymetry) and outside it. Outside the riverbed, the LiDAR data led to an important improvement, but not so inside the riverbed. To overcome these deficiencies, different models with simplified bathymetry or modified inflow hydrographs were used. Here, we present a model that is based upon the calibration of the Manning's \(n\) value inside the riverbed. The use of abnormally low Manning's \(n\) values made it possible to reproduce both the extent of the flooded area and the flow depth value within it (outside the riverbed) in an acceptable manner. The reduction in the average error in the flow depth value from 50-75 cm (models without bathymetry and \"natural\" [PERSON]'s \(n\) values) to only about 10 cm (models without bathymetry and \"calibrated\" Manning's \(n\) values), was propagated towards a reduction in the estimation of direct flood damage, which fell from 25-30% to about 5%.  
flood risk; cultural heritage sites; bathymetric data; manning's roughness coefficient; hydrodynamic modelling +
Footnote †: journal: Applied Sciences
## 6 Conclusions  
In this paper, we propose AV-SSLT to localize and track the specific sound source in a cocktail party environment. In order to focus on the target of interest, we present a way by combining voiceprint recognition and face recognition to locate the sound source. To obtain high-quality audio of the target for downstream tasks such as speech recognition, we designed a motion module to control the robot's movement towards the target while keeping away from other sound sources in the environment. The effectiveness of AV-SSLT has been fully corroborated via extensive practical experiments, which is demonstrated by the higher success rate in locating a specific target, the closer distance to the target at the end of tracking and the lower WER of speech recognition at the end of tracking than its counterparts. However, we have to admit that our system fails in some cases, such as when the target speaker has their back to the camera. Meanwhile, there is still room for improvement in the accuracy of speech recognition. Our future work will focus on improving the accuracy of face recognition when the face is in extreme poses to increase the success rate of specific target localization and on designing the geometry of the microphone array to reduce the interference of noises from other directions.  
**Author Contributions:** Supervision, L.Z.; Writing--original draft, Z.S.; Writing--review & editing, L.Z. and D.W. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This work was supported in part by the National Natural Science Foundation of China under Grant 62272343 and Grant 61973235; in part by the Shanghai Science and Technology Innovation Plan under Grant 20510760400; in part by the Shuguang Program of Shanghai Education Development Foundation and Shanghai Municipal Education Commission under Grant 21 SG23; and in part by the Fundamental Research Funds for the Central Universities.  
**Institutional Review Board Statement:** Not applicable.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Method** & **WER** \\ \hline Going directly to the target & 32\% \\ Moving with motion module & 18\% \\ \hline \hline \end{tabular}
\end{table}
Table 6: Word Error Rates (WERs) of speech recognition at the end of tracking.
# Design of Mega-Constellations for Global Uniform Coverage with Inter-Satellite Links
## 4 Simulation and Results
### Simulation Studies and Results on Mega-Constellation Design
(**a**) Constellation with an orbital inclination of 90\({}^{\circ}\); (**b**) Constellation with an orbital inclination of 70\({}^{\circ}\); (**c**) Constellation with an orbital inclination of 50\({}^{\circ}\); (**d**) Constellation with an orbital inclination of 30\({}^{\circ}\). After accomplishing the preliminary design of a mega-constellation, calculate the minimum distance between any two satellites in the constellation according to the collision-avoidance constraints. Set the safe distance between satellites to be 10 km. A total of 176 groups of satellites have been counted as having a minimum distance less than this safe distance. Adjust the argument of latitude of anyone satellite in each group using 1\({}^{\circ}\) steps until the minimum distance between that satellite and all other satellites is greater than the safe distance. Finally, a mega-constellation that avoids the risk of self-collision is available. To illustrate the superiority of the mixed Walker constellation design approach proposed in this paper, we will compare it with the Walker constellation of the same magnitude. To this end, a Walker constellation was constructed with an orbital inclination of 90\({}^{\circ}\), an orbital altitude of 600 km, and consisting of 75 orbital planes, each containing 75 satellites, for a total of 5625 satellites. Figure 7 shows the 3D configuration of the two constellations and the position of the sub-satellite points on the Mercator projection map. Firstly, a comparison of 3D space images shows that the [PERSON] constellation is more regularly distributed in space. However, the dense distribution of satellites at high latitudes not only wastes space resources but also significantly increases the collisions risk between satellites within the constellation. The mixed Walker constellation designed by applying the method in this paper can spread relatively evenly over the surface of the celestial sphere. The satellites are roughly equally distributed over all latitude zones, greatly relieving the pressure of dense satellite distribution over high latitude regions. Secondly, comparing the 2D maps, it can be seen that the sub-satellite points of the [PERSON] constellation are completely uniformly distributed on the map, but since the Mercator projection is equiangular, its deformation increases with increasing latitude when representing distances, which means that the phenomenon [PERSON]'s sub-satellite points are evenly distributed at high latitudes is seriously distorted. In contrast, the distribution of sub-satellite points of the mixed [PERSON] constellation shows a gradual sparseness from low to high latitudes, which is more in line with the expectation that the constellation is uniform in space. Therefore, in terms of distribution, the mixed [PERSON] constellation designed in this paper is more conducive to uniform global coverage of the Earth.
## 2 Proposed VO System
### Solution Implementation
#### 2.3.1 Movement Estimation
However, it is possible that some false correspondences were made in the flow analysis process, introducing an error into the VO. Therefore, a filtering process is employed. This procedure operates under the principle that all key points from one image must comply with the transformation matrix \(T_{k+1,k}\). Specifically, any point that does not align correctly will exhibit a significantly larger reprojection error with the transformation matrix compared to other points. Consequently, the proposed algorithm discards all points whose reprojection error exceeds the mean error by more than one standard deviation. The results of this process are shown in Figure 2, where a cluster of mismatched features in the lower right side of the image is removed after the filtering is applied. Finally, after the filtering process, the transformation matrix \(T_{k+1,k}\) is recalculated.
# Immobilization of Levocyetririzine on Mesoporous Silica for Antiallergenic Gel Formulation
## 2 Materials and Methods
### Scanning Electron Microscopy (SEM) Measurement  
The starting materials and the synthesized mesoporous materials were characterized using SEM (Zeiss EVO40, Zeiss, Jena, Germany) equipment equipped with a tungsten hairpin filament operated at 20 kV. Working distance was set between 10 and 11 mm depending on the focus. Images were captured at various magnifications utilizing a secondary electron detector. Prior to analysis, the powders were sputter-coated with an ultrathin layer of gold to avoid electrostatic charging.
# Recent Developments in Materials Science for the Conservation and Restoration of Historic Artifacts
## 5 Biopolymers: Sustainable Conservation Solutions
### Case Studies
The study tested the protective coatings by examining surface morphology, color stability, and water contact angle, followed by accelerated aging treatments simulating exposure to solar, UV, and acidic environments. Among the three biopolymers, PLA showed superior hydrophobic behavior, indicated by the highest water contact angle, which effectively protected against pollutant interactions without affecting the marble's visual appearance. An analysis of samples from the statue confirmed that gypsum, primarily formed by reactions between calcite in marble and sulfur dioxide (SO\({}_{2}\)) in polluted environments, contributes significantly to black crust formation. PLA's hydrophobic properties provided a barrier, effectively limiting this SO\({}_{2}\)-calcium carbonate interaction, thus reducing the potential for black crust formation on the marble. PLA emerged as the most suitable candidate due to its ability to create a replicable, reversible protective layer. Its renewable origins and biodegradability align well with sustainable conservation practices, offering a promising alternative to petrochemical-based treatments commonly used in artifact preservation.
# Tablet Scoring: Current Practice, Fundamentals, and Knowledge Gaps
###### Abstract  
Oral solid dosage formulations and/or tablets have remained the preferred route of administration by both patients and health care practitioners. Oral tablets are easy to administer, they are non-invasive and cause less risk adversity. Because of the lack of commercially available tablet dose options, tablets are being split or partitioned by users. Tablet scoring refers to the breakage of a tablet to attain a desired efficacy dose and is an emerging concept in the pharmaceutical industry. The primary reason for the tablet scoring practice is to adjust the dose: dose tapering or dose titrating. Other reasons for tablet partitioning are to facilitate dose administration, particularly among the pediatric and the geriatric patient population, and to mitigating the high cost of prescription drugs. The scope of this review is to: (1) evaluate the advantages and inconveniences associated with tablet scoring/portioning, and (2) identify factors in the formulation and the manufacturing of tablets that influence tablet splitting. Whereas tablet partitioning has been a common practice, there is a lack of understanding regarding the fundamentals underpinning the performance of tablets with respect to splitting. Several factors can influence tablet partitioning: tablet size, shape, and thickness. A requirement has recently been set by the European Pharmacopoeia and the U.S. Food and Drug Administration for the uniformity of mass of subdivided tablets. For breaking ease, an in-vivo reference test and a routinely applicable in-vitro test need to be established.  
Keywords:pharmaceutics; formulation; tablet manufacturing; tablet splitting; drug administration +
Footnote †: journal: Applied Sciences