esa-sceva/satcom-chunk-collection huggingface dataset:
# Distance Estimation with a Stereo Camera and Accuracy Determination
## 2 Materials and Methods
The cup is 67 mm high and 105.5 mm wide (measured with the handle), with a diameter of 86.4 mm. The LEGO figure, on the other hand, is 40.3 mm high, 24.5 mm long, and 7.7 mm wide. Thanks to the discrepancy in the dimensions of the two test pieces, it will also be possible to assess the effect of the objects' dimensions on the precision of the measurements. The experiment was carried out for distances ranging from 20 to 70 cm, increasing the distance by 2.5 cm. Three measurements were made for each distance, allowing a large amount of data to be collected. Such accuracy and repeatability of the measurements enable reliable analysis and verification of the results, assessing the estimation of the distance between cameras and objects. With such a wide range of data, it is also possible to determine the impact of different distances on the accuracy of the measurement and the calibration of the system. The 20-70 cm distance range was chosen for its potential application in medicine, particularly in the analysis of mandibular mobility, where cameras mounted at a distance of about 30 cm can accurately monitor the movements of this structure. The selected range is also optimal for precise measurements in scenarios where objects are in close range, such as the analysis of limb movements or observation of small parts in rehabilitation. In addition, this range is ideal for monitoring isolated systems, such as finger or hand movements, where high accuracy is required close to the measuring device. In this way, the system can be used for both the detailed observation of small objects and the study of precise movements in confined spaces, expanding its potential applications in physiotherapy and rehabilitation.
## 3 Results and Discussion
### Field-Effect ICEO of a Janus micropillar Subjected to a Controllable Gate Voltage
#### 3.3.3 Effect of Driving Voltage on Janus AC-FFET at a Given Gate-Voltage-Bias Ratio \(\beta\)  
According to Equations (25)-(28), the ICEO flow rate has a second-order dependence on the AC-driven-voltage amplitude of the paired conducting DE plates embedded on the channel sidewalls, implying that it effectively enhances the ICEO flow rate by increasing the background electric-field intensity, as shown in Figure 7, with a given gate-voltage-offset ratio of \(\beta=0.8\) (\(V_{\mathrm{G}}=0.9V_{\mathrm{D}}\)), field frequency of 200 Hz, and pillar radius of \(\mathrm{R=5~{}\mu m}\) for varying \(V_{\mathrm{D}}\) from 0.5 to 3 V. Moreover, the electric-field strength reaches 30 V\(\cdot\)mm\({}^{-1}\). This order of magnitude of the AC-driven voltage implies that there is a sinusoidal voltage drop of 0.3 V across an insulating gap 10 \(\mu\)m in size, which is even lower than the common case of 1-1.5 V used in the experimental visualization of circulating AC electro-osmotic micro-eddies.  
To be more specific, both \(\mathrm{u_{x}}\) for horizontal transport and \(\mathrm{u_{y}}\) for lateral stirring rise quadratically with the applied driving voltage \(V_{\mathrm{D}}\) under a proportionally growing gate voltage \(V_{\mathrm{G}}=0.9V_{\mathrm{D}}\) for a given gate-voltage-offset ratio \(\beta=0.8\). One order of the applied electric field induces a Debye screening cloud within the IDL, and then the other order acts on the voltage-induced diffuse-space charge at the post/electrolyte interface to create nonlinear ICEO streaming, which survives even after time averaging in zero-mean AC fields. However, their common feature in second-order voltage dependence results in a constant ratio of \(\mathrm{\chi=u_{y}/u_{x}}\) independent of the driving voltage \(V_{\mathrm{D}}\) (Figure 7A), which suggests that it may not be effective in enhancing the device's mixing performance via a simple elevation of the driving voltage.  
In Figure 7B,C, the magnitude of IZP increases linearly with the \(V_{\mathrm{D}}\) due to the field-induced feature of bipolar IDL on the polarizable surfaces of both the dielectric and the metal phases of the Janus pillar. The action of the applied voltage on its own induced diffuse-screening cloud then leads to the stable convection of ICEO next to the target post, whose flow velocity increases much faster than the value of the IZP with the driving voltage when taking into account the quadratic voltage dependence of ICEO streaming (Figure 7B,D). The large difference in IZ and ICEO fluid motion between the dielectric and metal surfaces justifiably accounts for the physical origin of the active pump behavior \(\mathrm{u_{x}}\) in the broken symmetry of ICEO circulation along the channel length. Furthermore, the up-down symmetry breaking in the IZP (Figure 7C) and tangential ICEO slip (Figure 7D) at the metal-phase/electrolyte interface via the AC field-effect flow control is responsible for the generation of a net transversal rotating motion \(\mathrm{u_{y}}\) across the width of the channel.
## 2 Materials and Methods
### Fieldwork Conditions
#### 3.3.2 Slow-Turn Driving Scenarios  
A step signal from 0 to 0.1 was applied to the front axle to simulate the stability of the sprayer during emergency obstacle avoidance in its operation. Simultaneously, the sprayer was set to steer on a road surface with low adhesion, characterized by a coefficient of 0.3, while the vehicle maintained a constant speed of 5 km/h. The simulation duration was set to 10 s, with a time step of 0.001 s for the simulation. The simulation results are shown in Figure 15a-d, and representative parameters of the simulation results are summarized in Table 8.  
The analysis of Figure 15 and Table 8 indicates that the sprayer's low-speed steering performance without control significantly deviates from the ideal steering characteristics,  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Evaluation Indicators** & **No Control** & **PID + Average Distribution** & **SMC + Optimal Distribution** \\ \hline Maximum yaw rate & 0.035 & 0.021 & 0.003 \\ deviation/rad\(\cdot\)s\({}^{-1}\) & 0.060 & 0.057 & 0.054 \\ Maximum longitudinal & 4.585 & 0.304 & 0.165 \\ coordinate offset/m & & & \\ \hline \hline \end{tabular}
\end{table}
Table 8: Comparison of evaluation indexes under field operation—low-speed steering condition.  
Figure 15: State parameters of sprayer under field operation—low-speed steering condition: (**a**) input for the front axle angle; (**b**) horizontal swivel speed; (**c**) center of gravity side shift; (**d**) driving path.  
resulting in instability. The ideal yaw rate shows a step change at 2 s. The \"SMC + optimal distribution\" control method follows the ideal value most closely, with a maximum deviation of only 0.003, improving control by 85.7% compared to the \"PID + average distribution\" control. Additionally, the \"SMC + optimal distribution\" control method provides the best tracking of the centroid sideslip angle, with the smallest deviation from the desired trajectory, demonstrating superior control effectiveness.
## 9 Dispersion Compensation
### Chirped Mirrors  
In order to maintain near zero net GDD in the cavity, components of tuned negative GDD must be incorporated in the cavity. Chirped mirrors are a common component for dispersion compensation [59, 60], which are coated with a stack of dielectric layers, designed such that different wavelengths penetrate a different depth in the stack, as illustrated in Figure 9a. Mirrors are specified in the amount of negative GDD per bounce they provide. In many cases, a single mirror has a strong GDD oscillation across the spectrum, and pairs of mirrors are commonly designed with opposite oscillations, such that the combined GDD of the pair is spectrally smooth. The technology of dielectric coatings for the manipulation of ultrashort pulses has matured in recent years, and now, even double-chirped mirrors are available for Ti:sapphire cavities that provide specifically-tuned negative GDD to also compensate for higher order dispersion over an extremely wide spectral range, allowing one to achieve pulses with an extreme bandwidth (octave-spanning spectrum) [61, 62, 63]. Since compensation with chirped mirrors is discrete in nature (a finite dispersion per bounce on the mirror), one can use a wedge window pair to fine-tune the dispersion, as illustrated in Figure 9b. By controlling the insertion of one window, the variable thickness adds positive GDD in a controlled manner, allowing for continuous compensation.  
Figure 9: Dispersion compensation devices: (**a**) chirped mirrors; (**b**) a pair of wedged windows; (**c**) a pair of prisms.
# Big Data Collection in Large-Scale Wireless Sensor Networks
## 2 Overview of WSNs
### WSN Communication
#### 2.4.1 One-Hop Communication  
One-hop communications lead to transmissions over long distances resulting in a significant increase in energy consumption. Figure 4 illustrates this type of communication.
## 4 Performance Evaluation
### Buffer Management Evaluation
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Buffer Size**} & \multirow{2}{*}{**Drop Policy**} & \multicolumn{4}{c}{**Forwarding Policy**} \\ \cline{3-6}  & & **Random** & **FIFO** & **TTL** & **Smallest** \\ \hline \multirow{4}{*}{50 MB} & Random & 0.473 & 0.449 & 0.442 & 0.559 \\  & FIFO & 0.505 & 0.496 & 0.490 & 0.565 \\  & TTL & 0.472 & 0.445 & 0.440 & 0.582 \\  & Largest & 0.625 & 0.600 & 0.600 & 0.638 \\ \hline \multirow{4}{*}{100 MB} & Random & 0.538 & 0.519 & 0.519 & 0.607 \\  & FIFO & 0.557 & 0.548 & 0.535 & 0.618 \\ \cline{1-1}  & TTL & 0.558 & 0.544 & 0.533 & 0.621 \\ \cline{1-1}  & Largest & 0.634 & 0.619 & 0.610 & 0.645 \\ \hline \multirow{4}{*}{200 MB} & Random & 0.609 & 0.603 & 0.604 & 0.643 \\ \cline{1-1}  & FIFO & 0.616 & 0.607 & 0.604 & 0.643 \\ \cline{1-1}  & TTL & 0.619 & 0.608 & 0.607 & 0.647 \\ \cline{1-1}  & Largest & 0.632 & 0.616 & 0.612 & 0.649 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Delivery probability for a 24 h TTL (Time to Live) with different buffer sizes and queue policies. Figure 8: Delivery probability versus latency for a 12 and 24 h TTL (Time To Live) with different buffer sizes and queue policies.
# Enhanced Effective Filtering Approach (eEFA) for Improving HSR Network Performance in Smart Grids
## 2 Effective Filtering Approach (EFA)  
To significantly reduce redundant unicast traffic in HSR networks, EFA performs traffic filtering for all unused rings, including nondestination DANH rings and passive QuadBox rings.  
1. Filter traffic for nondestination DANH rings by using PL; and
2. Filter traffic for passive QuadBox rings by using FQR.  
In this study, for the purposes of operational descriptions, performance analysis, and simulations, we consider a sample HSR network that consists of eight DANH rings interconnected by QuadBoxes, as shown in Figure 1. In communication scenarios, source DANH 1 sends unicast frames to destination DANH 10.
## 5 Noise-Corrected Clustered-Sparse Channel Estimation
### Noise-Resistant Bayesian Channel Estimation  
As the number of pilots \(K_{p}\) decreases, the precision of channel estimation using the PB-CSBL algorithm will rapidly deteriorate. This is primarily because the algorithm does not utilize all the information available. Specifically, although both pilot and data symbols are transmitted, only the \(K_{p}\times M\) matrix \(\mathbf{Y_{P}}\) corresponding to the pilot subcarriers in (8) is used for estimating the CIRs. For the matrix \(\mathbf{Y}\) in (7), the remaining \(K_{d}\times M\) observations are typically not used as they contain the unknown data symbols. If the unknown data symbols are perfectly obtained, using the Bayes rule, the posterior mean of CIRs based on the prior probability in (17) and the channel measurement equation in (10) can be written by  
\[\overline{\mathbf{\mu}}_{\mathbf{h}}=\mathbf{\Sigma}_{0}\mathbf{U}^{H}\Big{(}\mathbf{ \Lambda}+\mathbf{U}\mathbf{\Sigma}_{0}\mathbf{U}^{H}\Big{)}^{-1}\mathbf{y}, \tag{32}\]  
with the posterior covariance matrix:  
\[\overline{\mathbf{\Sigma}}_{\mathbf{h}}=\mathbf{\Sigma}_{0}-\mathbf{\Sigma}_{0}\mathbf{U} ^{H}\Big{(}\mathbf{\Lambda}+\mathbf{U}\mathbf{\Sigma}_{0}\mathbf{U}^{H}\Big{)}^{-1} \mathbf{U}\mathbf{\Sigma}_{0}. \tag{33}\]  
Moreover, AWGN is assumed to simplify implementation complexity in the PB-CSBL algorithm, as the noise power distribution \(\mathbf{\lambda}=[\lambda_{-K/2},\lambda_{-K/2+1},\cdots,\lambda_{K/2-1}]\) depends on the observation of all subcarriers. However, in a complex UWA environment, the noise power may vary significantly over the signal bandwidth. Using decided data symbols and corrected colored noise, the high estimation accuracy can be achieved by the MAP estimate in (32).
# Technologies Trend towards 5G Network for Smart Health-Care Using IoT: A Review
## 4 Technology Trends to Achieve the Requirements in the 5G Network
### Millimetre-Wave Communications  
From Equation (1), it is clear that the channel with high bandwidth results in an enhanced data rate. However, for increasing the bandwidth of the channel, the higher operating frequency is required. It will solve the second trend for the next generation network (i.e., 5G) by using higher frequencies in the millimetre wave band. However, there are many disadvantages of millimetre wave communications. Firstly, having free-space propagation in the millimetre wave leads to higher signal attenuation [69]. Secondly, rain, atmospheric gases, and buildings are reasonable observers of this band [70]. For the problem, as mentioned above, different solutions are possible: using tiny cells will lead to minimising the attenuations; for higher attenuations, the directive antennas to be used or indoor base stations to avoid the building absorption issue.  
Figure 6: Massive MIMO and 3D MIMO.
# LIF-M: A Manifold-Based Approach for 3D Robot Localization in Unstructured Environments
## 5 Experimental Design and Results  
### Experimental Environment and Setup  
This section describes a series of experiments carried out to qualitatively and quantitatively analyze the localization framework proposed in this paper. The sensor suite that we used consisted of a combined handheld device comprising a depth camera (D435), a 16-line LiDAR sensor (Velodyne VLP-16), and an IMU (3 DM-GX5). As depicted in Figure 3, this platform served as the sensor data input source for algorithm validation.  
The geographical and point cloud structures are illustrated in Figure 4. The chosen experimental scene is surrounded by grassy areas, scattered trees, and moving vehicles. The roads exhibit irregularities, and the surrounding buildings often feature transparent glass elements. We anticipate that these nanostructured point clouds may pose a challenge to the localization system.  
By reducing the reliance on robot odometry in most localization algorithms, the approach described in this paper enhances the algorithm's overall versatility. Consequently, the algorithm presented here is equally applicable to a range of scenarios, including wheeled robots, legged robots, drones, and more.  
The experimental platform utilizes the NVIDIA Jetson AGX Xavier (with eight-core ARM CPU, 64-bit architecture, 32 GB RAM, 32 GB storage, and a 512-core Volta GPU) as the upper-level computer, running Ubuntu 20.04 as the operating system, and uses the ROS (Robot Operating System) Noetic middleware for data handling.
# Methods of Analyzing Microsized Plastics in the Environment
## 5 Emerging Technologies
### Nano Thermal Analysis  
Nano thermal analysis (nano-TA), a method of generating AFM images using nano-TA probes, is a local thermal analysis technique combined with high spatial resolution. Through this, an understanding of the thermal behavior of materials can be obtained with a spatial resolution of less than 100 nm. In nano-TA analysis, the probe moves to a fixed point on the sample surface when a point of interest is selected. The probe is very sensitive to the stiffness (hardness) of the microplastic. The tip heats up at a constant rate over time but stops heating when the sample surface reaches its glass transition temperature. It is mainly used to study the nanoscale surface properties of microplastics and to measure the glass transition temperature because the sample softens during phase inversion. Moreover, it is a method by which the probe penetrates the sample [81].  
Recently, a study on the effect of the characteristics of TiO\({}_{2}\)-dyed microplastics on the aging process and the properties of microplastics affected by the advanced oxidation process was conducted using nano-TA [72; 81]. The nano-TA analysis of microplastics provides information on the thermal properties of individual regions, such as glass temperature, which is useful in understanding the chemical composition and physical state of each region of microplastics.  
Semi-crystalline polymers of polycaprolactone (PCL), LDPE, polyoxymethylene (POM), PET, PS, polymethyl methacrylate (PMMA), polycarbonate (PC), and the like, and the phase transition temperature for amorphous polymers, have also been studied using the nano-TA analysis method [82].
# Satellite-Based Localization of IoT Devices Using Joint Doppler and Angle-of-Arrival Estimation
## 3 System Model  
In order to generate a Doppler signature, the satellite(s) need to be in relative motion to the user. As such, we focus on low-Earth-orbit (LEO) satellite constellations, assuming that the satellites have accurate knowledge of their own position/orbit. In this scenario, the satellites act as anchor nodes that attempt to localize the ground IoT devices by utilizing both the angle-of-arrival (AoA) and Doppler measurements. This section presents the constellation geometry, Doppler measurement model, and angle-of-arrival measurement model.
# Transaction Mechanism Based on Two-Dimensional Energy and Reliability Pricing for Energy Prosumers
## 3 ERT Implementation Issues
### Utility Side  
When applying the proposed ERT, the grid utility announces not only the energy price but also the reliability price and band for each operational time horizon. The energy price is determined by cost-balancing of the utility and prosumer, as under the existing pricing concept. The reliability price and band are decided considering utility requirements and prosumer characteristics.
# Technologies and Fabrication of Intelligent Packaging for Perishable Products
## 3 Printing Techniques
### Gravure Printing  
Gravure printing is a contact printing technique. It entails the direct transfer of functional links through physical contact of the engraved structures with the substrate [8] and provides higher resolution printing in comparison to noncontact printing. Thus, it may be used for the fabrication of printed devices with higher resistance and capacitance values. As shown in Figure 7, a gravure printer comprised a rolling cylinder and a printing cylinder. Firstly, the rolling cylinder is coated with copper. Following this, laser or electrochemical method is applied to engrave a pattern on the cylinder. The cylinder is then coated with a chrome layer for protection from wear and tear. The ink is introduced using an ink bath under the cylinder or a nozzle on top of the cylinder. A doctor's blade is applied to remove the excess ink. Finally, the ink is transferred to a rolling substrate [50]. [PERSON] et al. developed the functional ammonia, humidity, and nitrogen dioxide sensors, which were fabricated by screen and gravure printing on flexible poly substrates [84]. Ammonia and humidity sensors were fabricated by gravure printing of organic-based sensitive layers on flexible PET foil while the nitrogen dioxide (NO\({}_{2}\)) sensor was fabricated using screen printing.  
These printing techniques have been successfully employed to fabricate various types of flexible sensors. Recently, studies have been carried out on fabrication of printed sensors, especially for intelligent packaging. [PERSON] et al. applied inkjet printing to fabricate an RFID packaging coupling with a surface acoustic wave (SAW) sensor chip. Nanoparticle Ag ink was used to print the antenna structure onto the polymer package. The SAW sensor chip was fixed into the chip cavity. The result showed that the SAW package had a significant wireless response when antenna interrogated using a continuous waveform radar reader unit [85]. Therefore, printing is apractical and feasible method for large-scale and cost-efficient fabrication of intelligent packaging.
# Orbit Determination of Korean GEO Satellite Using Single SLR Sensor
## 1 Introduction
As Korea only has one available SLR station to obtain observation data of GEO satellites in Geochang, the OD of GEO satellites based on a single SLR station must be conducted. This study presents the OD of GK-2B based on a single station that satisfies the accuracy requirement. Figure 1 summarizes the flowchart of the OD procedure. The paper is organized as follows: In Section 2, SLR observation data simulation for GK-2B from Geochang SLR station is performed. In an effort to mimic the actual GEO satellite observations as closely as possible in the simulation, the observation data is generated based on quantitative observation data analysis for Compass-G1 GEO satellite. Two scenarios are configured with different numbers of SLR observations. In Section 3, OD of GK-2B based on simulated SLR observations is conducted for two scenarios. Also, to verify the validity of the derived OD strategy, the OD for Compass-G1 based on actual SLR observations from Changchun station is performed in Section 4. As Compass-G1 is part of the Global Navigation Satellite System (GNSS), a final precise orbit generated from International GNSS service (IGS) Analysis Center (AC) is obtainable. The estimated orbit from the OD process is externally compared with the final orbit from one of IGSACs and the resultant orbit overlap errors are quantitatively analyzed. Section 5 draws conclusions.
# Navigating the Maps: Euclidean vs. Road Network Distances in Spatial Queries
## 3 Methodology
### Euclidean Search
#### 3.4.1 K-Nearest Neighbors Search in Euclidean Distance  
The kNN queries method searched for the nearest POIs to the query point based on the number of points specified by the user, which was set to be limited to the first 20 data points (k = [1; 20]). These points were sorted based on their distances from the query point. The distances between query points and POIs were calculated on the database using the SQL statement presented in Listing 1.  
```
1 SELECT
2 ST_SETSRID(ST_MAXEPOINT(olon,olat),4326)::geography<->geom::geography
3 ASdist_eu
4 FROMhospital;
```  
**Listing 1** SQL statement for calculate Euclidean distance.  
In this statement, the \"geom\" column contains the geographical coordinates of individual hospitals, while \"olat\" and \"olon\" denote the latitude and longitude of the designated query point, respectively. Following the distance calculation, the results were ordered according to distance in ascending order, and only the top 20 data points were selected using the SQL statement shown in Listing 2.  
Figure 14: Left heatmap and query points from ambulance dataset; right heatmap and query points from hospital dataset in Perth.  
Figure 15: Left heatmap and query points from ambulance dataset; right heatmap and query points from hospital dataset in Sydney.  
```
1 SELECT*,
2 ST_SETSRID(ST_MAXEPOINT(olon,olat),4326)::geography<->geom::geography
3 ASdist_eu
4 FROMhospital_q1
5 ORDERBYdist
6 LIMIT20;
```  
**Listing 2** SQL statement for retrieving kNN result for Euclidean distance method.  
The retrieved data from this SQL statement represents the kNN search results for values of k between 1 and 20. For instance, the first row corresponds to the result of 1 NN, and the first to fifth rows collectively represent the result of 5 NN.