esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Seismicity Relocation
### Location Errors Estimation  
The location errors calculated by hypoDD are underestimated, usually being a few tens of meters. Thus, a bootstrap method was applied to the final residuals, creating a dataset by drawing samples from the observed residual distribution, adding them to the differential times and then repeating the relocation [15; 16]. This procedure was repeated 200 times and then the 95% error ellipsoid per event was computed by the resulting catalogs.  
The jackknife method [15] was also applied to evaluate the station distribution effect on the final catalog. The relocation was repeated omitting one station at a time, followed by a calculation of the standard deviations per event. The medians calculated for the axis of the ellipsoids produced by the bootstrap method and the medians of the standard deviations calculated from the jackknife method are summarized in Table 2.  
The errors produced by both methods show that in the west-east horizontal direction, they are much larger than in the north-south direction. This reveals the effect of the station distribution on the location accuracy, as the closer stations are located south of the activated area in the Lefkada and Kefalonia islands, in a rather narrow N-S oriented zone covering a small azimuthal range in the E-W direction. In addition, the number of stations is small to the east and north of the study area, in western Greece, and obviously there are no stations to the west, an area covered entirely by sea.
## 4 Results and Discussion
### Characterization of the Nano Biochar Nanoparticles
#### 4.1.2 Hydrodynamic Size and Zeta Potential  
The average hydrodynamic content or aggregates calculated via Dynamic Light Scattering (DLS) of biochar nanoparticles varies considerably from the diameter of a single  
Figure 2: Infrared Spectroscopy (FTIR) spectrum of the nano-biochar.  
biochar nanoparticle calculated using a TEM or image analysis techniques. As biochar nanoparticles are suspended in an electrolyte solution, they tend to agglomerate, forming aggregates of two or more particles depending on aggregation and synthetic cases in the suspension. DLS presumes the size of any particle (or aggregate of particles) with a certain equal diameter to be similar in size. Therefore, size average diameters determined via DLS cannot be directly compared to TEM diameters. TEM analysis revealed that the average size of biochar nanoparticles ranged between 30-70 nm, respectively (Figure 3). These characteristics are constant with results from prior studies in our laboratory for date palm waste biochar [29].
## 4 Experimental Results
### Evaluation of the Model with XAI Methods
#### 4.3.1 Explaining the Best Model with LIME
* The graphs for all credit scores indicate that the number of different types of bills paid by the customer, the type of bill, and the age of the customer are among the important features. When examining the LIME and SHAP outputs, the following conclusions can be drawn:  
* Customers with a habit of overdue payments have lower credit scores. * Customers with high credit scores prefer to pay their bills in cash. * As the number of days paid early increases, the credit score improves. * Each feature has a different level of importance in different labels. * The number of invoices for different types of bills in the relevant payment institution emerges as an important feature. Figure 5: _Cont._
# Research on Underwater Wireless Optical Communication Channel Model and Its Application
## 3 Underwater Optical Wireless Communication Experiment  
In order to verify the validity of this model, a series of trials are conducted in different water conditions, such as a pond, an inland lake, and near-shore areas, using trial equipment, like optical communication devices and a water quality attenuation tester. A dedicated test fixture was designed to provide the capability to position two modems underwater in arbitrary configurations relative to each other. The fixture- facilitates the precise translation of the transmitter with respect to the receiver at arbitrary ranges. The trial process commenced with the measurement of the attenuation coefficient of water. Subsequently, underwater optical communication trials were performed using the same optical communication devices to collect data on the effective communication space. These comprehensive trials served the purpose of verifying the accuracy and reliability of the model in predicting the behavior of underwater optical communication in real-world scenarios.
## 2 Description of the Used UGV Platform  
TAERO is basically designed for all-terrain operation in manned mode (with a driver). Depending on the combat situation, as well as military and non-military threats, the vehicle can be reconfigured into unmanned mode in a very short time (Figure 1).  
The vehicle is equipped with a central processing unit containing the necessary IT infrastructure, a precise GPS including an inertial navigation system (IMU), situation awareness sensors, and mechatronic drives adopted to manage factory-fitted mechanisms of the platform (Figure 2). The system has got a security module that authorizes access, allowing for management of the vehicle and its resources, as well as a set of high-data-rate radio systems that enable the transmission of control and vision signals with minimal delays. The architecture enables the integration of additional modules, e.g., an observation head, weapon systems, and a threat detection system.  
The vehicle is equipped with a hybrid drive: diesel (main) and electric (auxiliary) for silent operation. Durable and reliable four-wheel drive proven in the Polish Armed Forces, as well as rigid axles, differential lockers, and mud terrain tires equipped with runflats, guarantee high off-road capability in manned and unmanned modes (Figure 3).  
Figure 1: Model of the UGV platform. (**a**) Front view; (**b**) back view.  
Unmanned mode allows the following tasks to be carried out [15]:  
* Remote-controlled driving of a vehicle by an operator;
* Following a route saved during the manned or remote control mode;
* Autonomous waypoint navigation;
* Driving in \"follow me\" mode behind a soldier as a \"mule on wheels\" or behind another vehicle;
* Shuttle driving between designated points;
* Operation in front of a convoy;
* Driving in a tandem with an armored vehicle as a mobile control station;
* Reconnaissance and observation missions using additional equipment such as an observation head;
* Use of electric drive for silent operation.
## 3 Analysis and Design of the Force Control System
### Time-Varying Disturbances  
Another way to study the uneven characteristics of the surface is using sinusoidal disturbances \(x_{d}(t)=\sin(\omega t)\) (see Figure 4b). In this case, the velocity \(v_{y}\) at which the task is executed is proportional to the frequency \(\omega\) of the disturbance in the \(x\) direction. For example, the faster the end-effector is moving on the surface from point A to point B, the higher the frequency \(\omega\) of the sinusoidal disturbance. The proportionality relation depends on the wavelength \(\lambda\) of the sinusoidal, i.e., \(v_{y}=\lambda(\omega/2\pi)\).  
When a sinusoidal disturbance appears, the steady-state error \(e_{ss}\) cannot be used to analyze the force error, and the analysis presented in Section 3.1 is not valid. However, one can find a relation between the magnitude of the time-varying disturbance and the control gain/magnitude.  
Consider the following transfer function,  
\[\frac{F(s)}{X_{d}(s)}=\frac{KG_{LP}(s)G_{T}(s)}{1+G_{c}(s)G(s)KG_{LP}(s)G_{T}(s )},\]  
from the disturbance \(x_{d}\) to \(f\) (\(f_{d}=0\)). From [18], this transfer function can be approximated by \(\frac{F(s)}{X_{d}(s)}\approx\frac{1}{G_{c}(s)G(s)}\). Then, the disturbance \(X_{d}(s)\) can be attenuated by increasing the magnitude of \(G_{c}(s)\), since the goal is to have a magnitude,  
\[|F(s)|_{s=j\omega}=\frac{|X_{d}(s)|_{s=j\omega}}{|G_{c}(s)|_{s=j\omega}|G(s)|_ {s=j\omega}}, \tag{6}\]  
as close as possible to zero. Again, one should be aware of stability when the magnitude of the controller increases.  
Note that the computation of the magnitude \(|F(j\omega)|\) depends on the parameters of the controller \(G_{s}\), the dynamics of the robot \(G\), and the frequency \(\omega\). Whenever the mentioned parameters are available, one can obtain curves similar to those presented in Figure 5; an example of the curves is presented in Section 4.
# Pose-Based Gait Analysis for Diagnosis of Parkinson's Disease
## 2 Methodology
### Human Pose Estimation  
To track participants' motor performance in videos without using physical markers, we perform human pose estimation (HPE) using AlphaPose [19]. For a walking sequence of \(T\) seconds in which we track \(K\) body keypoints in a video with frame rate \(f\), HPE outputs a multivariate time series \(\{(x_{t}^{i},y_{t}^{i},p_{t}^{i})|i=1,\dots,K;t=1,\dots,fT\}\), where \((x_{t}^{i},y_{t}^{i})\) represent the 2D coordinates, and \(p_{t}^{i}\) is the detection probability of the \(i^{th}\) keypoint in frame \(t\). Due to the noisy nature of HPE data, smoothing is performed using a Savgol filter with a window size of 5. The motion of two subjects is illustrated in Figure 3.
## 6 Conclusions  
In this study, we adopted multi-sensor and multi-temporal InSAR observations combined with GNSS and groundwater level records to investigate land subsidence and its relations to sinkhole activity and groundwater depletion in the Karapinar basin, Turkey. We processed InSAR observations acquired by COSMO-SkyMed and Sentinel-1 from October 2014 to March 2018. The InSAR results reveal that the Karapinar region experienced significant land subsidence in 1-10 km wide patches, reaching rates of 70 mm/year. For both InSAR datasets, reliable subsidence rates were obtained over bare land that yielded high interferometric coherence. However, seasonal land-use changes in the Karapinar region resulted in wide decorrelated areas, mostly over agricultural land. Land subsidence results obtained from X-band COSMO-SkyMed and C-band Sentinel-1A detected similar rates and spatial patterns of subsidence. Temporal subsidence patterns, obtained from GNSS, COSMO-SkyMed, and Sentinel-1 time series, showed a continuous subsidence with a significant seasonal component, which correlate well with the temporal pattern of groundwater level change in the region. Our study indicates a significant increase in subsidence rate from 15 mm/yr during 2002-2010 [35] to 70 mm/yr during the period of 2014-2018 (this study). The relations between sinkhole activity and subsidence indicate that most sinkholes occur in decorrelated, agricultural areas or in areas with small subsidence rates. Sinkhole occurrence in slow subsidence areas reflects the strong cohesion of near-surface rock layers that resist subsidence but yield to collapse in response to aquifer system deformation induced by groundwater extraction.  
Conceptualization, O.O., S.W.; methodology, O.O., T.O.-C.; software, O.O., T.O.-C. and S.Y.; formal analysis, O.O., T.O.-C. and S.Y.; writing--original draft preparation, O.O., M.Y.; writing--review and editing, O.O. and S.W.; visualization, O.O.; supervision, S.W.; project administration, O.O., S.W. All authors have read and agreed to the published version of the manuscript.  
The authors appreciate the support provided by The Scientific and Technological Research Council of Turkey (TUBITAK, the program no;2214-A-1059B141601339) and the National Science Foundation (NSF) grants EAR-1620617 and EAR-1713420.  
Data Availability Statement: Data sharing not applicable.  
**Acknowledgments:** We thank the Italian Space Agency (ASI) and European space agency (ESA) for providing SAR images (COSMO-SkyMED and Sentinel-1, respectively). We are grateful to General Directorate for State Hydraulic Works, General Directorate of Mapping (GDM), and Harris Geospatial Solutions, Inc. for providing groundwater level data, GNSS data, and SARscape software respectively. This is contribution number 1003 from the Southeast Environmental Research Center in the Institute of Environment at Florida International University.  
**Conflicts of Interest:** The authors declare no conflict of interest.
## 3 Materials and Methods
### Model Initialization
#### 3.3.1 Study Area Selection  
To develop DDSM via MATSim, we need to filter and process initial demand and supply data. Since coverage areas of road network raw data and LBS that demand raw data are inconsistent, we first select a study area and perform temporal and spatial filtering of the raw data according to the area scope. We selected a study area in Hangzhou, China, the host city of the 19 th Asian Games in 2023. The research area covers an approximate area of 46.5 square kilometers above the Rainbow Expressway in Binjiang District of Hangzhou, including the river crossing road at the edge of the region. According to local government statistical yearbooks, the resident population within this area was about 338,000 people in the year 2021.
# A New Orbiting Deployable System for Small Satellite Observations for Ecology and Earth Observation
## 2 Small Satellites for VIS, TIR, and MW Remote Sensing  
Satellites can be classified according to their weight: large (mass > 1000 kg), medium (mass from 500 kg to 1000 kg), and small (mass < 500 kg). Small satellites, born as a mere curious experiment and which currently have a key role for space exploration [22; 26; 27], can be further classified, as reported in Table 1.
## 2 System Setup
### Camera System Setup  
For vision-based sensing, an IDS UI-3060 CP-C-HQ Rev. 2 industrial camera is used. They can record 166 frames per second with a resolution of 2.35 megapixels (\(1936\times 1216\)). Further technical data include a pixel size of 5.86 \(\upmu\)m, 11.3 mm \(\times\) 7.1 mm sensor dimensions, and an optical sensor class of \(1/1.2^{\prime\prime}\). For communication with the laptop PC a USB 3.0 port is provided.  
\begin{table}
\begin{tabular}{l l l} \hline \hline
**Module Name** & **Nom. Torque/Force** & **Max. Velocity** \\ \hline PR 90 (rotary) joint A \& B \& C & 44.8 Nm & \(\omega_{\text{max}}=25\,\text{rpm}\) \\ PR 70 (rotary) joint D & 10.0 Nm & \(\omega_{\text{max}}=25\,\text{rpm}\) \\ PW 70 (pan-tilt) joint E \& F & 12.0 Nm \& 2.0 Nm & \(\omega_{\text{max}}=25\,\text{rpm}\) \\ PG 70 (gripper) & 200 N & \(v_{\text{max}}=25\,\text{m/s}\) \\ \hline \hline \end{tabular}
\end{table}
Table 1: Technical properties of the Schunk modules.  
Figure 1: Experimental setup and configuration of the modular manipulator.  
The camera's position concerning the robot is chosen such that the image area covers all markers attached to the robot for the complete workspace of the robot. The spatial arrangement of robot and camera is shown in Figure 2, highlighted by arrows.  
The image area of the camera is shown in Figure 3 for several configurations of the robot arm at the outer bounds of the workspace. As illustrated by the drawn line, the outermost marker is within the image area for the whole workspace.  
The metallic surface of the foundation aluminum plate is covered by some black fabric in order to avoid light reflections that could cause problems in marker detection during image processing.  
For a two-dimensional workspace of the robot, as it is the case for the experimental studies done in this paper, a single camera is sufficient for measuring the position. As soon as three-dimensional movements are allowed, a second camera for stereo vision is required.  
Before the camera can be used for position estimation, the visual system has to be calibrated once utilizing a checkerboard pattern of known size. Thereby, both the internal and external camera parameters are identified, such as for example focal length and coordinate transformations.  
Figure 3: Image area with the end-effector in several positions at the outer bounds of the workspace. All markers are visible for the whole workspace.  
Figure 2: Arrangement of robot and camera in the experimental setup from two perspectives highlighted by arrows.
###### Abstract  
As the peak of solar cycle 25 approaches, increased ionospheric and scintillation activity is being observed, which is negatively impacting the quality of GNSS measurements and presenting challenges in the positioning domain. Ionospheric refraction and diffraction introduce delays and distortions to GNSS carrier phase measurements, leading to positioning errors that exceed the anticipated accuracies. These position errors can be a significant concern for users across the world who depend on precise GNSS positioning, such as in agriculture, offshore marine positioning and autonomous automotive positioning. To understand the direct impact on NovAtel receivers and its positioning engines, a comprehensive analysis was conducted. A closer look was taken at what happened in 2023-2024 by characterizing scintillation using the amplitude scintillation index (S4) values in an equatorial region. Additionally, the scintillation effect on the receivers was characterized through the analysis of C/N0, lock breaks, double differences and other indicators. With a substantial amount of data collected at 20\({}^{\circ}\) latitude, where high solar activity occurs due to the proximity to the equator, the positioning performance of Real-Time Kinematic (RTK) and Precise Point Positioning (PPP) was analyzed.  
Keywords:ionospheric scintillation; carrier phase; code phase; RTK; PPP +
Footnote †: Corresponding author: Email: [EMAIL_ADDRESS]
## 6 Experimental Results
### Performance Evaluation
#### 6.3.8 MobInfoSec Protocol  
The MIS protocol has the following delay values: \(D_{1}=2,D_{2}=3,D_{3}=4\). We have identified four paths that indicate a Man-in-the-Middle behaviour (locations 195, 1345, 1763, or 2463 are reachable), twenty-four paths representing an honest execution (locations from 1 to 24 are reachable), and 380 paths representing execution with the Intruder.  
For this protocol, we have observed that values \(L_{1}=L_{2}=L_{3}=11\) and \(L_{4}=11\) are the only values that allow all the honest executions (these values do not allow a Man-in-the-Middle behaviour). The minimum values that allow a Man-in-the-Middle behaviour to appear (locations 1345, 1763, or 2463 are reachable) are \(L_{1}=L_{2}=L_{3}=L_{4}=12\).  
The minimum values that allow all Man-in-the-Middle behaviours to appear (locations 195, 1345, 1763, or 2463 are reachable) are \(L_{1}=L_{2}=L_{3}=L_{4}=13\).
## 3 Materials and Methods
### Database and Subrogated Model  
In this work, two patient databases are presented and used. The first one, called fragmented hypertrophic cardiomyopathy (FHCM) database, is compounded by 80 standard twelve-lead ECG records which were collected, analyzed, and diagnosed by expert clinicians in our group from Hospital Clinico Universitario Virgen de la Arrixaca (Murcia, Spain). These records were selected from a larger databasecompounded by 225 patients with standard twelve-lead ECG records, and we selected those ones which were in electronic format. The demographic data of the complete database were \(47.0\pm 15.9\) years and men-to-women ratio of 152/73. These ECG were recorded with GE-MAC 5000 system from General ElectricTM, at 500 Hz sampling rate and 4.88 \(\upmu\)V resolution. An example of fragmented ECG and non-fragmented ECG in FHCM database can be seen in Figure 1a,b, respectively. The second database, called Control database, is compounded of the first 200 records from a database of 418 standard twelve-lead ECG from students of Universidad Catolica de Murcia, where the demographic data of the complete database were \(23.1\pm 4.3\) years and men-to-women ratio was 314/104. These ECGs were recorded with ELI 350 system from MortaraTM and digitized at 1000 Hz sampling rate and 2.5 \(\upmu\)V resolution. An example of control ECG can be seen in Figure 1c.  
In addition to the before described databases, in this work we developed a new set of signals, so-called subrogate modeled signals, which comprise the control records after their artificial modification by adding a synthetic fragmented-wave component. This fragmented wave was added randomly in terms of number of the leads affected and of the time-slot in the QRS complex where it was located. The function used for the fragmented-wave component follows the expression of a simple sinusoid, as follows,  
\[F(t)=A\cdot\sin\left(\frac{\pi nt}{w}\right) \tag{1}\]  
where \(A\) is a random number between 1% and 30% of the main peak amplitude, \(t\) is the time vector an its values going from 0 to 2\(w\), \(w\) is a random number between 4 ms and 24 ms that represents the fragmentation duration, and \(n\) represents the number of semi-cycles of the sinusoid. An example of synthetically fragmented ECG can be seen in Figure 1d.  
Figure 1: Example for each type of used register in this work. (**a**) Example of a beat without fragmentation. (**b**) Example of a fragmented beat. (**c**) Example of a beat from control patient. (**d**) Example of a synthetically fragmented beat.
## 3 Results
### FE Analysis for Mode I, Mode II, and Mixed-Mode Tests
This is similar to the fracture surface based on the locations of the initial crack initiation and crack growth shown in Figure 11b. Figure 15b illustrates the shape of the average stress on critical point with respect to crack growth, which indicates that the crack propagated nonlinearly in the center as well as on the edge at the length of 45 mm and beyond. This phenomenon was observed in the crack growth located near the loading point, and similar crack growth behaviors were confirmed in the test and the analysis. In Figure 16a,b, which show the displacement-load curve as the analysis result of the Mixed-mode and the crack growth behavior and fracture toughness, respectively, it can be observed that the test and analysis exhibited similar trends. In the test, a 3 mm pre-crack  
Figure 14: Comparative analysis of specimen-level FE analysis results and Mode II test results: analysis result shape of Mode I: (**a**) \(P-\delta\) curve and (**b**) \(G_{II}-a\) curve. Figure 15: FE analysis result shape of Mode II: (**a**) in-plane stress contour and (**b**) crack growth length at applied displacement. test was performed to ensure the homogeneity of the initial crack shape. Additionally, the analysis considered that crack growth behavior was confirmed from 25 mm (including pre-crack length) because crack propagation was generally simulated as a cohesive failure. On the other hand, in Figure 17, crack growth was observed as the stress propagated from the center of the specimen to the edge. Figure 17a shows the initial crack selection, the shape of the final crack, and the in-plane stress as the principal stress, and Figure 17b shows the crack growth behavior with respect to the applied displacement and the average stress at the critical point. Particularly, Figure 17b shows a similar trend as the fracture surface shown in Figure 11a based on the locations of the initial crack and crack growth. In other words, the reliability of the crack growth model in the Mixed-mode was established by confirming the similarity between the progressive fracture analysis method implemented through a finite element analysis and the test. Therefore, to reduce the deviation of the test and analysis results at the initial crack location, lamination patterns and surface treatment with a relatively smaller bridging effect in the test are required. Consequently, it is believed that the characteristics of the composite-adhesive-joint failure must be considered when evaluating the durability of the blades for a wind turbine.