esa-sceva/satcom-chunk-collection huggingface dataset:
# Image Motion Measurement and Image Restoration System Based on an Inertial Reference Laser
## 2 Principle of Image Motion Measurement Based on Inertial Reference Laser  
The image motion measurement method based on inertial reference laser relies on a laser reference system with an inertial sensor. The reference laser and imaging light are introduced into the optical system by the same path, and the image motion information can be measured directly and used to drive the image stabilization mirror for real-time compensation. Based on the available image motion information, the image is restored via post-processing to reduce the impact of chatter on the image quality.  
The principle of the image motion measurement method based on an inertial reference laser is illustrated in Figure 1. Specifically, a reference laser beam is emitted by the inertial reference laser unit and introduced into the camera through the corner cube prism. The reference beam and imaging light pass through the same optical path (primary mirror, secondary mirror, and image stabilizing mirror, etc.) and then reach the position sensitive detector (PSD) located at the edge of and rigidly fixed to the camera focal plane. The PSD detects the jitter information of the reference laser beam, carries the motion information of the reference beam relative to the focal plane, and then fuses the camera attitude information measured by the inertial reference laser unit. This integrated information controls the image stabilization mirror through closed-loop feedback, and the image stabilization mirror compensates for the effects of flutter on imaging through fast motion in order to obtain excellent remote sensing images. Meanwhile, based on the available image motion information, image restoration software is used to restore the degraded images and to reduce the impact of on-orbit flutter on the imaging.  
As shown in Figure 2, the inertial reference laser unit mainly includes a high-precision inertial sensor and a laser source. The sensitive axes of the two-axis inertial sensors are located perpendicular to each other and are used to accurately measure the attitude change and jitter of the camera in two vertical directions within the integration time. The laser source is used to emit a reference laser beam. Given that the laser is rigidly connected to the inertial sensor, the absolute direction of the laser beam in the inertial space can be accurately measured.  
Figure 1: Principle of the image motion measurement method based on an inertial reference laser.  
Figure 2: Model of the inertial reference laser unit.
# Percolation Distribution in Small-World Quantum Networks
###### Abstract  
Quantum networks have good prospects for applications in the future. Compared with classical networks, small-world quantum networks have some interesting properties. The topology of the network can be changed through entanglement exchange operations, and different network topologies will result in different percolation thresholds when performing entanglement percolation. A lower percolation threshold means that quantum networks require fewer minimum resources for communication. Since a shared singlet between two nodes can still be a limitation, concurrency percolation theory (ConPT) can be used to relax the condition. In this paper, we investigate how entanglement distribution is performed in small-world quantum networks to ensure that nodes in the network can communicate with each other by establishing communication links through entanglement swapping. Any node can perform entanglement swapping on only part of the connected edges, which can reduce the influence of each node in the network during entanglement swapping. In addition, the ConPT method is used to reduce the percolation threshold even further, thus obtaining a better network structure and reducing the resources required.  
small-world quantum networks; entanglement swapping; quantum entanglement percolation; concurrence percolation theory +
Footnote †: journal: Applied Physics Letters  
0000-0002-4000-3399-2000][PERSON]  
0000-0001-5998-2000][PERSON]  
0000-0002-3399-2000][PERSON]
## 4 LTC Architecture  
### Overview  
Figure 1 depicts the proposed LTC system. The LTC system is based on the PoT architecture proposed in [8], and it inherits its enabling technologies and modular design philosophy. LTC consists of a PoT gateway, a set of WiFi-enabled RFID door-entry nodes distributed along with the entrances of the rooms within the premise, and assistive cloud-hosted services (namely, MongoDB database and Dialogflow's chatbot agent). The door entry nodes are connected to the PoT gateway through Wi-Fi. The PoT gateway acts as an MQTT broker that relays user logs at door entry nodes (publishers) to the cloud-hosted MongoDB instance (subscriber). User logs include their RFID tag numbers, the ID of the door entry that publishes the log, and the timestamp of the log occurrence. The cloud-hosted database maps the user tracking, based on their RFID tag numbers, to the extension number(s) at their current location, depending on the ID of the door entry node that pushes the log information. Upon dialing a preconfigured hotline extension number, the call is auto answered by the embedded Asterisk server of the PoT gateway, and it invokes a developed Python script. The script saves the user's utterance as an audio file, sends it to the developed Dialogflow's chatbot agent, and waits for a reply. The chatbot agent recognizes the user's intent, identifies entities in the user speech, and determines the target employee to be called based on the exact name mentioned or the question asked by the calling person. The chatbot then sends a webhook request to the cloud-hosted database querying the extension number at the current location of the target person to be called. Upon reception of the extension number, the Dialogflow chatbot sends a text file to the PoT gateway that contains the extension number. The Python script reads the received response file from Dialogflow and extracts the extension number. The script then passes the extension number to the Asterisk server running on the PoT gateway to originate a call to that extension number and pass the call to the calling person. The following subsections delineate the system's components and highlight the motivation behind the choice of the enabling technologies they utilize.
## 5 Results and Discussion
### Analysis of Results among DE Variants
\begin{table}
\begin{tabular}{c c c c} \hline
**Case Study** & **Variant** & **Min \(\epsilon\) (mm)** & **Max \(\epsilon\) (mm)** \\ \hline \multirow{6}{*}{C1} & rand/1/bin & 1.5791 \(\times\)\(10^{-2}\) & 1.2610 \(\times\)\(10^{-1}\) \\  & rand/1/exp & 1.9585 \(\times\)\(10^{-4}\) & 5.5990 \(\times\)\(10^{-4}\) \\  & best/1/bin & 1.0844 \(\times\)\(10^{-3}\) & 1.3547 \(\times\)\(10^{-2}\) \\  & best/1/exp & 6.0853 \(\times\)\(10^{-4}\) & 7.3483 \(\times\)\(10^{-3}\) \\  & current-to-rand/1 & 2.0705 \(\times\)\(10^{-2}\) & 9.0178 \(\times\)\(10^{-2}\) \\  & current-to-best/1 & 1.5673 \(\times\)\(10^{-2}\) & 7.1780 \(\times\)\(10^{-2}\) \\  & current-to-rand/1/bin & 1.5285 \(\times\)\(10^{-2}\) & 1.7790 \(\times\)\(10^{-1}\) \\  & rand/2/dir & 9.4962 \(\times\)\(10^{-2}\) & 3.4111 \(\times\)\(10^{-1}\) \\ \hline \multirow{6}{*}{C2} & rand/1/bin & 7.9554 \(\times\)\(10^{-2}\) & 6.1321 \(\times\)\(10^{-1}\) \\  & rand/1/exp & 7.9865 \(\times\)\(10^{-2}\) & 6.1541 \(\times\)\(10^{-1}\) \\  & best/1/bin & 7.9865 \(\times\)\(10^{-2}\) & 6.1541 \(\times\)\(10^{-1}\) \\  & best/1/exp & 7.9865 \(\times\)\(10^{-2}\) & 6.1541 \(\times\)\(10^{-1}\) \\  & current-to-rand/1 & 7.9714 \(\times\)\(10^{-2}\) & 6.1540 \(\times\)\(10^{-1}\) \\  & current-to-best/1 & 3.1867 \(\times\)\(10^{-2}\) & 6.5551 \(\times\)\(10^{-1}\) \\  & current-to-rand/1/bin & 7.9873 \(\times\)\(10^{-2}\) & 6.1545 \(\times\)\(10^{-1}\) \\  & rand/2/dir & 7.9215 \(\times\)\(10^{-2}\) & 6.1579 \(\times\)\(10^{-1}\) \\ \hline \multirow{6}{*}{C3} & rand/1/bin & 4.3437 \(\times\)\(10^{-2}\) & 1.8433 \(\times\)\(10^{-1}\) \\  & rand/1/exp & 1.3298 \(\times\)\(10^{-4}\) & 6.6972 \(\times\)\(10^{-3}\) \\  & best/1/bin & 3.1495 \(\times\)\(10^{-4}\) & 8.3755 \(\times\)\(10^{-3}\) \\  & best/1/exp & 5.7835 \(\times\)\(10^{-2}\) & 2.9000 \(\times\)\(10^{-1}\) \\  & current-to-rand/1 & 3.3445 \(\times\)\(10^{-2}\) & 3.7868 \(\times\)\(10^{-1}\) \\  & current-to-best/1 & 1.4906 \(\times\)\(10^{-1}\) & 6.3833 \(\times\)\(10^{-1}\) \\  & current-to-rand/1/bin & 1.7922 \(\times\)\(10^{-2}\) & 8.9935 \(\times\)\(10^{-2}\) \\  & rand/2/dir & 1.6952 \(\times\)\(10^{-1}\) & 1.5012 \\ \hline \multirow{6}{*}{C4} & rand/1/bin & 1.1348 \(\times\)\(10^{-1}\) & 3.6744 \(\times\)\(10^{-1}\) \\  & rand/1/exp & 1.8390 \(\times\)\(10^{-1}\) & 6.5760 \(\times\)\(10^{-1}\) \\  & best/1/bin & 1.1160 \(
## 2 Related Work
Firstly, we introduce complex-valued structures into the GAN so that both the generator and discriminator can fully leverage the inherent phase-related information in complex signals to extract RFF features with greater representational ability. Secondly, the generator of the CC-GAN effectively removes random dynamic noise from the signals and generates noise-free signals through symmetrical upsampling and downsampling structures. Finally, the discriminator of the CC-GAN extracts more robust and adaptive RFF features from the noise-free signals for identification. Consequently, the CC-GAN can significantly enhance the identification performance of target satellites in dynamic noisy environments.
## 3 Analysis of Accuracy and Performance
### Analysis of VLF Amplitude and Phase Characteristics  
The propagation-phase characteristics of VLF electromagnetic waves in the ionosphere are studied by using a vertical electric dipole source of a single-frequency signal.
## 4 Identifying sections with different level of vulnerability  
The two obtained datasets, represented by \"kinematics\" zoning map and damage map, as indicators respectively of ground instability intensity and linear infrastructure response, are merged in a qualitative \(4\times 4\) vulnerability matrix with a different value threshold of vulnerability, which provides a preliminary zoning map of different \"vulnerable sections\". In particular, once the two datasets have been separately analyzed, the new matrix, by means of four different vulnerability levels, allows to characterize current damage susceptibility to ground movements (Figure 2).  
It is important to highlight that such analysis can be performed only for pixels of fishnet in which satellite and damage data are available, in order to characterize both kinematics of ground movement.  
According to such criterion, qualitative suggestions regarding intervention measures suitable to the different vulnerability levels can be provided:  
* \"Low\" vulnerability level: Acceptable. A periodical monitoring of ground kinematics and a control of in situ conditions can be recommended. No mitigation options need to be considered;
* \"Moderate\" vulnerability level: May be tolerable. A periodical monitoring and controlling slope stability and in situ conditions with a higher frequency can be required and planning treatment options may be defined to maintain or reduce vulnerability;
* \"High\" vulnerability level: A detailed investigation, planning, and implementation of measures to vulnerability reduction is required;
* \"Very High\" vulnerability level: An extensive and detailed investigation and an expensive planning of stabilization measures are essential to reduce vulnerability to acceptable levels. Linear infrastructure could be useless.
## 2 Materials and Methods
### Salt and Dye Rejection Experiments  
The salt and dye rejection methodologies were conducted in a similar way to the one described for the BSA filtration experiment in the Sterlitech HP4750 Stirred Cell (Auburn, WA, USA). For salt rejection, 100 mL of 0.5 mg/mL MgSO\({}_{4}\) solution or Na\({}_{2}\)SO\({}_{4}\) solution (500 ppm) was permeated through R-HIPS membranes at 30 psi, whereas for dye rejection, a 100 mL solution containing 0.05 mg/mL of Reactive Black 5 (50 ppm) was used. The permeation and retention fluxes of salt solution were calculated using Equations (9) and (10):  
\[\mathrm{J}\;=\;\frac{\mathrm{V}}{\mathrm{A\cdot t}} \tag{9}\]  
\[\mathrm{R}(\%)=\left(1-\frac{\mathrm{C_{p}}}{\mathrm{C_{f}}}\right)\times 100 \tag{10}\]  
where \(C_{p}\) is the concentration of salt or dye in the permeate, and \(C_{f}\) is the salt or dye concentration in the feed. Salt rejection was measured using a conductometer. In the dye rejection experiments, concentrations were determined using a UV-Vis spectrometer at 595 nm.
# Urban Traffic Signal Control under Mixed Traffic Flows: Literature Review
## 2 Research Methodology  
### Open Questions and Scope Definition  
As mentioned, this review paper is focused on the analysis of the impact of mixed traffic flow on TSC in urban areas. Reviewed papers analyze the applicability of CV as data sources for adaptive traffic signal control, as well as the impacts of mixed traffic flow on traffic signal control and urban dynamics. To accomplish the research's objectives, the following research questions were defined:  
* RQ1: What are the intersection state estimation approaches?
* RQ2: What is the impact of mixed traffic flows on urban traffic dynamics?
* RQ3: How to process large amounts of data quickly and efficiently using the potential of CVs and CAVs as mobile sensors?
## 3 Methodology
### Evaluation Metrics  
The model's performance was assessed using standard classification metrics, including precision, recall, F1-score, and accuracy, calculated as follows:  
\[Precision=\frac{TP}{TP+FP}, \tag{4}\]  
\[Recall=\frac{TP}{TP+FN}, \tag{5}\]  
\[F1\text{-}Score=2\times\frac{Precision\times Recall}{Precision+Recall}, \tag{6}\]  
\[Accuracy=\frac{TP+TN}{TP+TN+FP+FN} \tag{7}\]  
where TP represents true positives, TN as true negatives, FP as false positives, and FN as false negatives.  
Figure 3: Data flow in a LSTM autoencoder.  
Precision measures the proportion of correctly identified anomalies, while recall evaluates the model's ability to detect all true anomalies. The F1-score balances precision and recall, particularly in imbalanced datasets, and accuracy provides an overall assessment of classification correctness. Together, these metrics ensure a comprehensive evaluation of the model's effectiveness in detecting stuck pipe events. These evaluation metrics were selected due to their established effectiveness in previous studies for assessing anomaly detection models [56, 57, 58].
# Train-Induced Vibration Analysis and Isolation Trench Measures in Metro Depot Structures
## 3 Propagation Law of Train-Induced Vibration in Metro Depot  
### Verification of Model Calculation Accuracy  
To better reflect the accuracy of the model calculation results and the reliability of the vibration propagation patterns, a comparison is made between the calculated results and the measured results for the metro depot model. The verification points are located at the footing of the track area structural column and the top of the cover structure column, both situated near the depot entrance, as shown in Figure 8. In this study, the background interference vibration elimination method is applied to ensure the accuracy of train-induced vibration measurement data in the depot area. The specific steps are as follows: First, the acceleration at the verification point is measured when no trains are operating, and this is defined as the background interference vibration baseline. Next, the acceleration at the same verification point is measured again during train operation, and both datasets are subjected to Fourier Transform (FFT). The frequency spectrum components corresponding to the background interference vibration are then subtracted in the frequency domain to eliminate the influence of background noise. Finally, the Inverse Fourier Transform (IFFT) is applied to reconstruct the time-domain signal, enabling the acquisition of accurate train-induced vibration measurement data.  
Figures 9 and 10 show the acceleration time history comparison and the vibration level of 1/3 octave band comparison at the two verification points, respectively. For verification point 1 (footing of the track area structural column), the measured peak acceleration is 0.0154 m/s\({}^{2}\), while the calculated peak acceleration is 0.0143 m/s\({}^{2}\), with an error of 7.7%. For verification point 2 (top of the cover structure column), the measured peak acceleration is 0.0225 m/s\({}^{2}\), while the calculated peak acceleration is 0.0245 m/s\({}^{2}\), with an error of 8.9%. The errors between the measured and calculated peak acceleration values at both points are within 10%. From the vibration level of 1/3 octave band comparison, it can be observed that the maximum vibration levels in the 1/3 octave band at both verification point 1 (footing of the track area structural column) and verification point 2 (top of the cover structure column) occur at 40 Hz. Within the frequency range of 2-80 Hz, the simulated  
Figure 7: Wheel-rail force of train wheelsets.  
vibration levels closely match the measured values. In summary, the metro depot model can effectively simulate the vibration issues caused by trains returning to the depot.
## 1 Introduction  
Since Kesling first invented the aligner in 1946, an aligner for tooth alignment has been developed [1]. Recently, patient demand has increased for more orthodontic treatments with esthetic appliances [2]. In line with this, Align Technology Inc. (San Jose, CA, USA) launched the Invisalign system in 1999, which enables esthetic orthodontic treatment because traditional braces are not invisible. This was the first CAD (computer-aided design) and CAM (computer-aided manufacturing)-based orthodontic appliance, which can be digitally scanned, and made as a series of aligners using a single impression [3, 4].  
The approximate digital manufacturing process of a clear aligner is as follows. First, a digital image is obtained by scanning a plaster model taken either by direct impression of the patient's dentition with a three-dimensional (3D) scanner or by directly scanning the patient's dentition with an intraoral scanner. When the digital model is created in this way, the file can be loaded in the setup program to start making the clear aligner [4,5]. Following the setup program, the crown, root, and long axis are set, and the teeth are moved to the desired position, which is the final arrangement. After that, a series of clear aligners suitable for the treatment period is designed. At this stage, it is recommended that the tooth rotation is within 2.5 degrees and the movement distance confined to 0.3 mm at each stage [6]. After that, a 3D printer is used to make a model for step-by-step changes and then make a series of progressive clear aligners to move the misaligned teeth.  
Recently, increasing numbers of patients are receiving orthodontic treatment with clear aligners, including those patients undergoing orthognathic surgery. Although there have been many studies showing that the postoperative stability of orthodontic patients treated with conventional fixed orthodontic devices is good [7,8], there have been no studies on postoperative stability of orthodontic patients treated with clear aligners. In this preliminary study, the stability and characteristics of patients using clear aligners after orthognathic surgery were investigated.
# LPCP: An efficient Privacy-Preserving Protocol for Polynomial Calculation Based on CRT
## 8 Performance and Evaluation
### Practical Performance
\begin{table}
\begin{tabular}{l l l l} \hline \hline
**Arithmetic** & **Running Time of** & **Running Time of** & **Total** \\
**Operation Type** & **ARM Architecture** & **X86 Architecture** & **Communication** \\ \hline
32-bit add & 1.219 ms & 0.1779 ms & 89B \\
32-bit mul & 1.268 ms & 0.1931 ms & 89B \\
32-bit exp & 1.279 ms & 0.2098 ms & 89B \\
64-bit add & 1.395 ms & 0.2387 ms & 111B \\
64-bit mul & 1.54 ms & 0.2366 ms & 111B \\
64-bit exp & 1.651 ms & 0.2969 ms & 111B \\
128-bit add & 2.189 ms & 0.484 ms & 155B \\
128-bit mul & 2.171 ms & 0.4693 ms & 155B \\
128-bit exp & 2.346 ms & 0.5529 ms & 155B \\
256-bit add & 5.716 ms & 2.0154 ms & 243B \\
256-bit mul & 5.845 ms & 2.0358 ms & 243B \\
256-bit exp & 6.79 ms & 2.3488 ms & 243B \\
1024-bit add & 213.43 ms & 85.376 ms & 771B \\
1024-bit mul & 221.993 ms & 86.446 ms & 771B \\
1024-bit exp & 238.629 ms & 86.21 ms & 771B \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Performance of LPCP on additive, multiplicative and exponential operations.
## 2 RS Systems
### Active
#### 2.2.2 Scatterometer  
Scatterometers are active microwave sensors and measure the backscattering coefficient (\(\sigma^{\circ}\)). \(\sigma^{\circ}\) depends on the dielectric and geometric characteristics of the incidence surface [42]. Generally, two architectures, namely, fan-beam and pencil-beam, have been considered to develop spaceborne scatterometers [43]. Fan-beam provides a fixed number of azimuths which look over a range of incidence angles (i.e., 20\({}^{\circ}\) to 60\({}^{\circ}\)) by employing multiple antennas. Pencil-beam collects \(\sigma^{\circ}\) values at two different incidence angles and wide azimuthal angles by a single rotating antenna. In terms of antenna configuration, spaceborne scatterers are generally categorized into three groups: (1) the multiple fixed fan-beam scatterometers with constant azimuth angles [44]; (2) the rotating pencil-beam scatterometers with inflexible incidence angle [45]; and (3) the rotating fan-beam scatterometers, which offer a large swath coverage, increase the variety of observation geometry, and boost scanning speed [46].
## 3 Numerical Calculation Models
### Material Parameters  
In the model, the cold joint interface adopts a pre-compiled cohesive fatigue damage element, while other regions use the Concrete Damaged Plasticity (CDP) model. The CDP model describes the non-elastic behavior of concrete by combining damage elasticity under isotropic conditions with tensile and compressive plasticity [30; 31; 32]. It is commonly used to analyze the mechanical response and deformation of concrete structures under cyclic and dynamic loading conditions. The elastic and plastic parameters input into the CDP model in the computational software are as follows: Elastic modulus \(E_{0}=30000\) MPa, Poisson's ratio \(v=0.2\), Dilatation angle \(j=38^{\circ}\), Eccentricity \(e=0.1\), Ratio of biaxial compressive strength to uniaxial compressive strength \(f_{b0}/f_{c0}=1.16\), Invariable stress ratio \(K=0.667\), Viscous parameter \(\alpha=0.00005\).
# A Novel Scheme for MIMO-SAR Systems Using Rotational Orbital Angular Momentum
## 5 Discussion  
Based on RDE, a novel scheme of the OAM-based MIMO-SAR system is proposed in this paper. In Section 2, a simplified 2 \(\times\) 2 model is established, which is a MIMO-SAR with two transmit and two receive channels that together provide three virtual phase centers. More antennas can be used to increase the number of observation channels, which could further enhance the performance of the OAM-based MIMO-SAR system.  
The proposed scheme is verified at a proof-of-concept level, through the RDE experiments referred to SISO and MISO modes. In the experiments, the rotational OAM beam was implemented by rotating the SPP mechanically, and thus the rotation speed cannot be very high, which limits the rotational Doppler frequency shift. The virtually rotational UCA antenna scheme introduced in Section 3 is a more suitable way to generate the desired rotational OAM beams.  
Note that in Figure 9, apart from two main lobes, other harmonic frequency components also exist, which indicates that the transmitted OAM beam from SPP is not of pure OAM mode. The main OAM mode accounted for the highest proportion, while other OAM modes give some minor contributions, which can also be filtered in the frequency domain.