esa-sceva/satcom-chunk-collection huggingface dataset:
# A Phase Correlation Anti-Noise Displacement Estimation Method Based on PSD Phase Screening
## 2 Methods
### PSD-Based Phase Screening  
The cross-power spectrum matrix obtained in the previous section is a complex matrix with a phase that is a periodic toothed fringe signal. The displacement between the two images can be estimated based on the toothed fringe signal. The fringe is clear under ideal conditions, but there will be a lot of speckle noise in the fringe due to the presence of noise during image acquisition. In some extreme cases, the fringe is not visible at all, which makes it is uncertain to estimate the displacement.  
In view of the serious noise interference of the cross-power spectrum matrix, this paper utilizes PSD to evaluate the clarity of the phase fringes and then screen out the cross-power spectrum matrix regions with clear fringes, based on the evaluation results. According to the definition of PSD [40], to calculate every element in the phase of the cross-power spectrum matrix, a neighboring window with \(w\times w\) has to be considered, per Equation (4). In the equation, \(\overline{\varphi}(i,j)\) is the phase gradient of each element in the window \(w\times w\) (the average value of the gradient of the direction \(x\) and \(y\)); \(w\) is the window size (w is experimentally set to 7), and \(\varphi(i,j)\) is the phase of the current element. The PSD matrix and the phase of its corresponding cross-power spectrum matrix are shown in Figure 3; where Figure 3a is the cross-power spectrum matrix's phase, Figure 3b is the PSD matrix.  
\[\sigma_{\varphi}=\sqrt{\frac{S_{\varphi}}{w^{2}-1}}\qquad S_{\varphi}=\sum_{i=1 }^{w}\sum_{j=1}^{w}[\varphi(i,j)-\ \overline{\varphi}(i,j)] \tag{4}\]  
According to the calculated PSD matrix, the most central element is taken as the seed point, and \(t\) percentage of the variance of the PSD matrix is used as the seed growth threshold (\(t\) can be adjusted with different amount of noise; it is experimentally set to 50 in this paper). A region-growing algorithm [46] is performed to obtain the clear stripe area  
Figure 3: Cross-power spectrum and corresponding PSD, where (**a**) is the cross-power spectrum matrix’s phase, and (**b**) is the PSD matrix.  
in the cross-power spectrum matrix, and the smallest bounding rectangle of the area is cropped for subsequent processing. The phase matrix is shown in Figure 4.
## 3 Analysis and Design of Key Components  
### High-Temperature and Ultrahigh-Pressure Simulation Test Cabin  
With the requirements of high-pressure resistance and a large pressure vessel, the material and structure of the pressure vessel must be strictly controlled. In practical engineering, vessels with design pressures between 10 and 100 MPa are generally called high-pressure vessels, and those with design pressures exceeding 100 MPa are called ultrahigh-pressure vessels. The maximum working pressure of the coring simulation test chamber proposed in this paper is 140 MPa, so it belongs to the category of ultrahigh-pressure vessels.
# Survey on Unmanned Aerial Vehicle for Mars Exploration: Deployment Use Case
## 4 Simulation Results and Discussion
### Sensors Block  
The sensor block is designed as per the requirement for Mars exploration through the designed UAV prototype. The sensor block includes various sensors' configurations. In our proposed model, we have included sensors, such as Inertial Measurement Unit (IMU), camera, pressure sensor, and an ultrasound sensor, which are discussed below:
## 4 Results
### RAG Module Effectiveness (Qualitative Examples)  
The effectiveness of the Contextualization Engine (CE/RAG) in improving response quality and safety through \"Positive Filtering\" was assessed qualitatively. Representative rule-document pairs were selected from the PoC's knowledge resources, which include a policy repository defining potentially problematic query types, a knowledge base containing curated factual or neutral information, and rule-document linkage data associating specific rules with relevant contextual documents. Questions designed to potentially trigger a negative rule (identified in the policy repository) were posed to the system, once with RAG disabled and once with RAG enabled (utilizing the explicitly linked documents from the knowledge base as context). Table 7 presents illustrative examples of this process. In general, responses generated with RAG context demonstrated improved neutrality, better factual grounding based on the provided documents, and alignment with safer perspectives contained within the linked context. This contrasts with the potentially problematic, evasive, or less-informed responses generated without RAG when faced with sensitive or complex queries. These qualitative results highlight the potential of using curated context, retrieved via the CE/RAG mechanism based on input analysis, not only to enhance factual accuracy but also to serve as a proactive safety mechanism, guiding the LLM towards more responsible and appropriate outputs. \begin{table}
\begin{tabular}{c c c c} \hline
**PII Type** & **Precision** & **Recall** & **F1-Score** \\ \hline Name & \textasciitif{}0.94 & \textasciitif{}0.92 & \textasciitif{}0.92 \\ \hline Phone Number & \textasciitif{}0.98 & \textasciitif{}0.97 & \textasciitif{}0.97 \\ \hline Email Address & \textasciitif{}0.97 & \textasciitif{}0.95 & \textasciitif{}0.96 \\ \hline Address & \textasciitif{}0.93 & \textasciitif{}0.90 & \textasciitif{}0.91 \\ \hline Card Number & \textasciitif{}0.99 & \textasciitif{}0.98 & \textasciitif{}0.98 \\ \hline Macro-Avg.* & \textasciitif{}0.96 & \textasciitif{}0.94 & \textasciitif{}0.95 \\ \hline \end{tabular}
* Macro-average calculated across all tested PII types.  
\end{table} 
Table 6: Performance of the AVI PoC’s PII detection mechanism on a synthetic dataset (n = 70 sentences).
###### Abstract  
A novel method is proposed for measuring the six degrees-of-freedom (DOF) geometric motion errors of a rotary axis based on a polyhedral prism. An error-sensitive unit which consists of a polyhedral prism and a planar reflector, is designed to carry out measurement of all six DOF errors, including the angular positioning error, the tilt motion error around the Y axis, the tilt motion error around the X axis, the radial motion error along the X and Y axes, and the axial motion error along the Z axis. The mathematical error model, including the six DOF geometric motion errors of the rotary axis, the installation errors between the polyhedral prism and the rotary axis, the manufacturing errors of the polyhedral prism, and the position errors of the sensors, are established. The effectiveness of the proposed method and the compensation model was simulated and experimentally verified.  
error measurement; six degrees-of-freedom motion errors; rotary axis; error model +
Footnote †: journal: Applied Sciences  
17 March 2021  
Accepted: 23 April 2021  
Published: 27 April 2021  
MOP1 stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.
## 8 NS2 Simulation Study
### Comparative Analysis of the Simulation Results
#### 8.2.2 Comparative Analysis of the End-to-End Delay  
The end-to-end delay \((EED)\) is measured as \"the average time taken by the data packets to arrive at a receiving node from a sender node, and it is mathematically expressed in the form \(\sum_{i=1}^{\
u_{p}}(T_{rec_{i}}-T_{send_{i}})/\
u_{p}\), where \(T_{rec_{i}}\) and \(T_{send_{i}}\) are the receiving and sending time of a packet \(i\), respectively, and \(\
u_{p}\) the total number of packets\". From the simulation results provided in Figure 5b, it was observed that \(EED\) values for the schemes of [PERSON] et al. [3], [PERSON] et al. [21], [PERSON] et al. [18], [PERSON] and [PERSON] [39], [PERSON] et al. [41], and LDAKM-EIoT were 0.17230 s, 0.15151 s, 0.12478 s, 0.12496 s, 0.13707 s, and 0.11640 s, respectively. The \(EED\) value of LDAKM-EIoT was less than the schemes provided in [3; 18; 21; 39; 41]. This was again due to the reason that LDAKM-EIoT applied small sized messages for the authentication procedure, which caused less end-to-end delay as compared to other schemes.
## 2 Results  
### Impact of Diosgenin on Bacterial Growth  
The effect of diosgenin on the growth of _Staphylococcus aureus_ was assessed by monitoring the absorbance at 600 nm (Abs\({}_{600}\)) over a 12 h period in cultures treated with 80 uM and 160 uM diosgenin (Figure 1). In the control group, treated with ethanol only, bacterial cultures exhibited typical exponential growth, reaching an Abs\({}_{600}\) of 11.1 after 8 h. Treatment with 80 uM diosgenin resulted in a slight but statistically significant reduction in bacterial growth, with the Abs\({}_{600}\) reaching 9.5 at 8 h. This suggests that 80 uM diosgenin exerts a mild inhibitory effect on bacterial proliferation without substantially arresting growth. A more pronounced inhibitory effect was observed in cultures treated with 160 uM diosgenin, with Abs\({}_{600}\) values at 8 h reduced to 8.9, representing a further reduction in bacterial growth below that of the 80 uM treatment group. The trend indicates that diosgenin exhibits concentration-dependent suppression of bacterial growth under these conditions. Despite the observed Abs\({}_{600}\) reductions, the bacterial cultures continued to exhibit growth over the 12 h period at both diosgenin concentrations, suggesting that the inhibitory effects of diosgenin were bacteriostatic rather than bactericidal under the tested conditions.
# Low-Complexity Pupil Tracking for Sunglasses-Wearing Faces for Glasses-Free 3D HUDs
###### Abstract  
This study proposes a pupil-tracking method applicable to drivers both with and without sunglasses on, which has greater compatibility with augmented reality (AR) three-dimensional (3D) head-up displays (HUDs). Performing real-time pupil localization and tracking is complicated by drivers wearing facial accessories such as masks, caps, or sunglasses. The proposed method fulfills two key requirements: low complexity and algorithm performance. Our system assesses both bare and sunglasses-wearing faces by first classifying images according to these modes and then assigning the appropriate eye tracker. For bare faces with unobstructed eyes, we applied our previous regression-algorithm-based method that uses scale-invariant feature transform features. For eyes occluded by sunglasses, we propose an eye position estimation method: our eye tracker uses nonoccluded face area tracking and a supervised regression-based pupil position estimation method to locate pupil centers. Experiments showed that the proposed method achieved high accuracy and speed, with a precision error of <10 mm in <5 ms for bare and sunglasses-wearing faces for both a 2.5 GHz CPU and a commercial 2.0 GHz CPU vehicle-embedded system. Coupled with its performance, the low CPU consumption (10%) demonstrated by the proposed algorithm highlights its promise for implementation in AR 3D HUD systems.  
eye tracking; eye detection; image occlusion; autostereoscopic 3D display; augmented reality +
Footnote †: journal: Applied  
**Keywords:** eye tracking; eye detection; image occlusion; autostereoscopic 3D display; augmented reality
## 4 Discussion
### Mechanical Properties of the Root System
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & **CK** & **S30** & **S60** & **S90** & **S120** & **S150** & \(p\) \\ \hline \multicolumn{8}{c}{First-order lateral roots (FL)} \\ Upslope & 9.33 \(\pm\) 1.75 a & 9.34 \(\pm\) 1.66 a & 9.29 \(\pm\) 1.56 a & 9.29 \(\pm\) 3.07 a & 9.37 \(\pm\) 1.26 a & 9.30 \(\pm\) 1.16 a & 0.30 \\ Downslope & 9.26 \(\pm\) 2.11 a & 9.31 \(\pm\) 2.31 a & 9.25 \(\pm\) 1.48 a & 9.27 \(\pm\) 2.28 a & 9.28 \(\pm\) 1.58 a & 9.25 \(\pm\) 1.39 a & 0.941 \\ \multicolumn{8}{c}{Non-embedded secondary lateral roots (NESL)} \\ Upslope & 13.39 \(\pm\) 2.16 a & 13.39 \(\pm\) 1.38 a & 13.41 \(\pm\) 2.11 a & 13.41 \(\pm\) 2.19 a & 13.41 \(\pm\) 3.31 a & 13.44 \(\pm\) 1.23 a & 0.858 \\ Downslope & 13.36 \(\pm\) 1.67 a & 13.34 \(\pm\) 1.29 a & 13.38 \(\pm\) 2.16 a & 13.36 \(\pm\) 1.47 a & 13.31 \(\pm\) 2.27 a & 13.28 \(\pm\) 1.36 a & 0.821 \\ Embedded secondary lateral roots (ESL) & 14.12 \(\pm\) 3.28 a & 14.56 \(\pm\) 2.41 a & 15.13 \(\pm\) 3.16 a & 15.87 \(\pm\) 2.22 a & 16.25 \(\pm\) 3.83 a & 16.78 \(\pm\) 1.51 a & 0.849 \\ Downslope & 13.41 \(\pm\) 2.56 a & 13.39 \(\pm\) 2.67 a & 13.37 \(\pm\) 3.08 a & 13.33 \(\pm\) 1.25 a & 13.29 \(\pm\) 2.28 a & 13.27 \(\pm\) 1.49 a & 0.739 \\ \hline \hline \end{tabular}  
* The tensile strength values in the table are calculated from equation (1) in 2.3. Data are the mean \(\pm\) S.E., \(n\) = 5. For each parameter, means with the same letter indicate no significant difference (\(p\) > 0.05). All letters in this table are “a”, indicating that the data are not significantly different.  
\end{table} 
Table 3: Comparison of tensile strength of lateral roots in different directions. is greater than that of downslope, and the tensile strength of upslope roots increases with increasing dosage, while the tensile strength of downslope roots decreases. We speculate that the difference in tensile strength between upslope and downslope lateral roots is related to wood fiber ratio and xylem fiber area, and the specific effects should be further explained after measuring the lignin and cellulose content and xylem fiber area in different lateral roots.
# Integrated Optical Phased Arrays for Beam Forming and Steering
## 8 Applications & Potential Alternatives
### Applications  
Integrated OPAs possess stable, rapid, and precise beam steering with the removal of mechanical components, making them robust and insensitive to external turbulences. As a low-cost high-performance solution to beam steering, integrated OPAs generate narrow beams. Many applications based on integrated OPAs have been implemented, from free-space communications, LiDAR, imaging, biological sensing, to special beam generation.
# Vehicle Route Planning for Relief Item Distribution under Flood Uncertainty
## 4 Experiment
### Simulation of Flood Uncertainty  
The effectiveness of the route plans produced using VRP-RIDFU is evaluated by simulating the uncertainty of flood conditions. This uncertainty relates to the likelihood that each section of the road will flood. Reduced travel speeds may result in longer wait times if the route plan under evaluation has several sections of flooded roads.  
This uncertainty is simulated to occur over time, with the time intervals generated randomly according to a uniform distribution. In this test, the number of occurrences of uncertainty ranges from 1 to 10 times. The maximum travel time of the optimal solution's route is used to define the time intervals for the occurrence of uncertainty. In other words, if there are five vehicles or five routes, the travel time of the route with the most extended duration is used to determine the time intervals for uncertainty occurrence. The road conditions in the simulated scenarios will vary randomly, making it challenging to predict.
## 3 Results
### LDH Release Level  
The LDH release assay was chosen to evaluate the toxicity of the tested compounds. LDH is a cytoplasm enzyme and the detection of LDH in the medium is an indicator of a loss of cell membrane integrity. The increase in LDH release is proportional to toxicity of the compound.  
BJ cells treated with 50 uM and 100 uM of Les-4368 for 24 h were characterized by a significant 48.15% and 68.63% increase in the LDH release level, respectively, compared to the control (Figure 4A). After the 48 h treatment of the BJ cells with 10 uM, 50 uM, and 100 uM of Les-4368, the LDH release level increased by 30.44%, 114.59%, and 145.30%, respectively, compared to the control (Figure 4A).  
After the 24 h exposure of the BJ cells to Les-4370, the level of LDH release increased at the 10 uM, 50 uM, and 100 uM concentrations by 27.82%, 35.14%, and 53.31%, respectively, compared to the control (Figure 4B). In turn, after 48 h, a 38.98%, 73.54%, and 30.04% increase in the level of LDH was observed at the same concentration of Les-4370, i.e., 10 uM, 50 uM, and 100 uM, respectively, compared to the control (Figure 4B).  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Cell Line** & **Tested Compound** & **Exposure Time** & \
\begin{tabular}{c} **IC\({}_{50}\)** \\ (\(\overline{\alpha}\)\(\pm\)**SD, \(\mu\)M**) \\ \end{tabular} &
\begin{tabular}{c} **LD\({}_{50}\)** \\ (\(\overline{\alpha}\)\(\pm\)**SD, \(\mu\)M**) \\ \end{tabular} \\ \hline \multirow{4}{*}{BJ} & Les-4368 & 24 h & 27.82 \(\pm\) 6.34 & 54.50 \(\pm\) 9.94 \\ \cline{2-5}  & 48 h & 15.46 \(\pm\) 7.83 & 19.95 \(\pm\) 5.38 \\ \cline{2-5}  & Les-4370 & 24 h & N/A & 87.75 \(\pm\) 4.65 \\ \cline{2-5}  & 48 h & N/A & 15.82 \(\pm\) 1.62 \\ \hline \multirow{4}{*}{CACO-2} & Les-4368 & 24 h & N/A & N/A \\ \cline{2-5}  & 48 h & 29.58 \(\pm\) 9.45 & N/A \\ \cline{2-5}  & 48 h & N/A & N/A \\ \cline{2-5} \cline{2-5}  & Les-4370 & 48 h & N/A & N/A \\ \hline \hline \end{tabular}
\end{table}
Table 1: The LD\({}_{50}\) values (uM, calculated based on the LDH release level) and IC\({}_{50}\) (uM, calculated based on the resazurin reduction results) of Les-4368 and Les-4370 compounds in BJ and CACO-2 cells after 24 h and 48 h treatment. N/A—not applicable (uncalculatable).  
After the 24 h treatment of the CACO-2 cells with Les-4368, the level of LDH at the 10 \(\upmu\)M, 50 \(\upmu\)M, and 100 \(\upmu\)M concentrations increased by 11.85%, 36.49%, and 38.08%, respectively, compared to the control (Figure 4C). In turn, the CACO-2 cells treated with 50 \(\upmu\)M and 100 \(\upmu\)M of Les-4368 were characterized by a 34.86 and 36.45% increase in this parameter, respectively, compared to the control (Figure 4C).  
A 23.53% increase in the LDH release level in the Les-4370-treated CACO-2 cells was observed only after 24 h in the 100 \(\upmu\)M concentration variant, compared to the control (Figure 4D).  
Based on data from the released LDH level, the half-maximal lethal dose (LD\({}_{50}\)) was calculated (Table 1).
## 5 Discussion
### Strengths, Weaknesses, and Future Studies  
As discussed earlier, there was no public dataset available for bamboo; this was overcome by creating our real bamboo dataset. Second, relatively few single or multiple ML/DL models have been studied for bamboo classification. In this work, we adopted five DL- and five ML-based models with the MajMulVot algorithm to improve the classification performance on the bamboo dataset. In addition, the DL technique was compared to the ML technique, with the DL technique demonstrating remarkable performance. This illustrates that automated feature creation and selection (DL) is better than handcrafted feature-based approaches (ML). This hypothesis may be considered to save effort and time in the feature creation selection process. Furthermore, the final DL model with MajMulVot gave the best result when we compared and validated it using the UC Merced Land Use Dataset. This illustrated that the MajMulVot approach outperformed the others when the multiple model option was available.  
MajMulVot is independent of the number of layers and the model architecture; however, if we require a time-efficient model that enhances the overall performance, then it is necessary to select all the base models with lightweight parameters. Furthermore, we applied this proposed model to a dataset of ten species with only 2000 samples. Our model will obtain more accurate results if more species datasets are available with more images to be sampled.
# Long-Term Behavior of Concrete Containing Wood Biomass Fly Ash
## 2 Materials and Methods
### Concrete Mix Design  
WFA was stored in the laboratory for a period of about two months before being used in concrete. During storage, WFA was sealed in plastic bags and then stored in closed plastic containers.  
The cement used in this study was Portland cement CEM I 42,5 R, according to the European standard EN 197-1:2011 [37]. The aggregate was crushed dolomite with an average bulk density of 2.8 kg/dm\({}^{3}\) and an absorption of 0.5%, 0.7%, and 0.3% for fractions 0/4, 4/8, and 8/16 mm, respectively. The aggregate grading curves were the same as presented in [2] and are therefore not repeated here.  
The composition of the concrete mixes is given in Table 2. The mixes had the same water/(cement + WFA) ratio of 0.5. Mixes containing WFA were prepared with cement replacement percentages of 15% and 30%. Mixes M1 and M2 were made with WFA1 and mixes M3 and M4 with WFA2.  
All constituents were conditioned to a temperature of 20 \(\pm\) 2 \({}^{\circ}\)C before mixing. Mixing was carried out in a compulsory mixer with a capacity of 75 L, following the mixing procedure specified in the standard EN 480-1:2014 for the preparation of reference concrete [38]. First, the aggregates and about half of the water were mixed for 2 min. After a two-minute break, mixing was continued with the addition of cement and WFA. After 30 s, the remaining water was added and mixing continued for 2.5 min.
# Improved PR Control Without Load Current Sensors and Phase-Locked Loops for APFs
## 3 A PLL-Less Load Current Sensorless Improved PR Control
### PR Controller Parameter Design
Compared with the traditional method, the proposed method significantly simplifies the controller design and system structure by using a single PR controller to compensate for all harmonics, reduces the computational burden, and improves the dynamic response and steady-state accuracy of the system. Through discrete modeling and root locus analysis, this section further explores the influence of proportional gain \(K_{\rm p}\) and resonant gain \(K_{\rm r1}\) on the pole distribution and stability of the system and proposes the optimal parameter selection range of \(K_{\rm p}\in[10,\,100]\) and \(K_{\rm r1}\in[10,\,100]\). This design method effectively improves the tracking accuracy and dynamic compensation performance of the reference current and ensures the stability of the system.