esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Numerical Modelling and Analysis
### Analysis of Numerical Calculation Results  
(1) Load-Displacement Curve  
As depicted in Figure 16, the numerical analysis results reveal that the displacement obtained from the finite element model follows a pattern consistent with experimental results as the load varies: the ultimate bearing capacity and ultimate displacement are close, with errors not exceeding 10%. Moreover, both exhibit consistent load-displacement variations, categorized into three stages: (1) linear elastic stage, during which displacement changes minimally, and the structure's stiffness remains unaffected. (2) Appearance and propagation of cracks stage, characterized by an increased rate of displacement growth and decreasing stiffness. (3) Failure stage, where the model is nearing failure, repair yielding occurs at the section, leading to a rapid increase in displacement and significant stiffness reduction.  
(2) Concrete Damage  
As shown in Figure 17, the plastic damage model for concrete material in the ABAQUS software effectively identifies the location of plastic damage in the model. Although this model cannot precisely determine the position of \"cracks\", it aids in identifying the location of damage, indicating the formation and expansion of cracks. At the ultimate load, as depicted in Figure 17, the damage locations in the model are consistent with the positions of cracks observed in experiments, mainly occurring at the interface of wet joints, both sides of the panel, and the bottom of the loaded position. Viewing from the side of the panel, damage mainly occurs at the section and extends to the loaded position. Figure 17a,b demonstrates that the simulated concrete damage locations align well with the experimental crack initiation and failure positions. Thus, this finite element model effectively simulates the loading process of the specimen, providing a modeling foundation for subsequent theoretical research.  
Figure 16: Comparison of load-displacement results.  
Figure 15: Tensile stress-strain curve of steel bar.
## 1 Introduction  
In the last two decades, the interest in the variation of the timing between beats (RR-intervals) of the cardiac cycle, called heart rate variability (HRV), has widely increased in the psycho-physiological research field. Assessment of RR-intervals variability is possible through time and frequency domain analyses that provide parameters able to quantify the amount of fluctuations occurring between consecutive beats, giving therefore an indirect index of autonomic regulation. Actually, the parameters extracted from HRV analysis are useful to provide insight about sympathetic-parasympathetic balance of cardiac vagal tone that was found to be an indicator of cognitive, emotional, social and health status [1].  
Thanks to the technological advancements of recent decades, it is now possible to continuously record heart activity during peoples' life via wrist-worn wearable devices equipped with heart rate sensors. This innovation might have a great impact on the medical field because of the low cost of the devices and the possibility to obtain continuous passive measurements performed in an ecological setting, gaining an overview of the users' health status by assessing HRV features during their daily life [2]. These wrist-worn wearable devices, however, produce several inconsistent RR-intervals produced not only by ectopic beats (e.g., atrial fibrillation and premature heart beat), but mainly by motion and mechanical artifacts induced by external stimuli. The number of abnormal RR-intervals increases from 1%--when heart beats are recorded with gold standard technology (i.e., electrocardiography)--[3] to more than 10%--when they are recorded with wrist-worn wearable devices. However, standard methods for calculating HRV features from the time-series of RR-intervals require accurate beat detection. Hence, handling the missing values became a fundamental aspect to correctly evaluate users' physiological response. As a matter of fact, these missing values affect the HRV analysis producing misleading results [4]. In previous studies, the inconsistent RR-interval data were handled by reconstructing the missing values using nearest-neighbour, linear, cubic spline and piecewise cubic Hermite interpolation methods [4; 5]. However, these methods can also introduce changes in the reconstructed timeseries that could corrupt the signal spectrum [6], thus reducing the ability to estimate both time or frequency domains HRV features.  
In this paper, we focus on healthy subjects with normal heart activity, and investigate the effects of interpolation on time (i.e., the timestamps when the heartbeats happen) and duration (i.e., the duration of the heartbeats) with an increasing amount of missing values (from 0% to 70%) in order to assess which interpolation strategy yields better results when estimating HRV features. In particular, in this paper we show that quadratic interpolation on time is the best approach to reconstruct the missing RR-intervals. Anyway, the main finding of this study is that the interpolation on time produce better HRV feature estimation that the interpolation on Duration suggested by all the previous studies.
# Nearly Linear-Phase 2-D Recursive Digital Filters Design Using Balanced Realization Model Reduction
## 5 Illustrative Examples and Numerical Evaluation  
In this section, we present several design examples to illustrate the effectiveness of the proposed method. In these examples, 2-D FIR lowpass, bandstop, and fan digital filters are first designed using window methods, and then the reduced-order 2-D IIR filters are obtained by using the proposed method. The implementation of the resulting filter designs is investigated and evaluated with respect to the maximum ripple in the passband region \(\Delta_{p}\), the maximum ripple in the stopband region \(\Delta_{s}\), the maximum ripple of the group delay in the passband region \(\Delta_{\tau}\), and the number of arithmetic operations.
## 3 Results and Discussion  
### ERT Field Acquisition and Data Analysis  
#### 3.1.1 L1 Survey Line  
The result of the L1 survey line, according to [PERSON], is shown in Figure 3 (RMS Error = 2.3%). The electrical property of the stratum is approximately divided into two layers, and the resistivity profile descends as the depth increases. There are two higher resistivity regions located at the survey line 10-18 m and 34-42 m, within 1.5 m depth from the surface. Because Kinmen Island had been free of rain for a long time in the measurement period, the topsoil was very dry. The other region shows low resistivity values at 3-18 m and 32-42 m of survey line and within 1.5-7.9 m underground. As the geology of this region is silty sand stratum, the geology is relatively loose and has higher water content. Notably, at 18-25 m of survey line and 2.5-6.5 m of depth, the resistivity value increases suddenly, the resistivity value of this region increases inwards, indicating this may be the tunnel location, according to preliminary analysis. According to Figure 3, the tunnel may be located at 2.5 m underground, with a height of about 2.5 m and a width of about 4 m, indicated by red dotted lines in Figure 3.
## 3 Results
### Attributing Changes in ET and GPP
The windspeed increased the GPP in spring and autumn and leads to a slight decrease in the GPP in summer and winter. The sunshine duration has a negative effect in summer and positive effects in the other seasons. Generally, the effects of atmospheric pressure, humidity and LUCC are relatively small compared to the above influence factors. The effects of the interactions of the factors on GPP should be of concern, as they can lead to a considerable decrease in GPP in spring, from March to May, and an increase in winter, in January and February. Overall, in spring, the precipitation is the dominant factor that increases GPP, while the temperature and eCO\({}_{2}\) also make great contributions, while the interactions have considerable effects on GPP reduction. The eCO\({}_{2}\) has a dominant effect on GPP increases in summer and autumn, followed by precipitation. Conversely, in winter, the temperature is the major factor that increases GPP, and the interactions of the factors should also be considered. Figure 12: Mean attributions of seasonal ET and GPP changes in the water source region of the Xiong’an New Area (**a**,**b**). \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Catchment** & **Atmospheric Pressure** & **Temperature** & **Humidity** & **Precipitation** & **Windspeed** & **Sunshine Duration** & **CO\({}_{2}\)** & **LUCC** & **Interact** \\ \hline BGC & 4.9\% & 15.9\% & \(-\)6.3\% & 57.7\% & 6.1\% & \(-\)4.8\% & 25.3\% & 0.3\% & 0.8\% \\ JMC & \(-\)8.1\% &
###### Abstract  
This paper deals with the trajectory tracking problem for a quadrotor unmanned aerial vehicle (UAV). For this purpose, two control strategies are proposed. First, a flight controller with a hierarchical structure is designed, whereby the complete closed-loop system is divided into two blocks. The system has an inner block for attitude control and an outer block for position stabilization, for a total of six proportional-derivative/proportional-integral-derivative (PD/PID) controllers. The second new trajectory tracking strategy is based on attitude stabilization. In addition to a direct stabilization of yaw and altitude, the \(x\) and \(y\) positions are stabilized by choosing an appropriate control of roll and pitch angles. The relations between positions \((x,y)\) and rotations (roll, pitch) are derived from the natural flight of the quadcopter. In this second approach, with only four controllers, the quadrotor UAV is able to follow any trajectory. In both approaches, the PD/PID controllers are synthesized using the genetic algorithm method, and compared with those obtained by the reference model method. Furthermore, a comparison between PD and PID controller performance is performed. Thereafter, the robustness of the proposed controllers is tested for trajectory tracking in a disturbed environment. Simulation results demonstrate that for the two approaches, PD controllers show a better behavior with respect to quadcopter stabilization than in trajectory tracking under different conditions.  
Keywords:quadcopter; hierarchical structure; reference model; genetic algorithm; trajectory tracking; PD/PID controllers; disturbances +
Footnote †: journal: Applied Physics Letters
# Measurements and Modeling of the Nonlinear Behavior of a Guitar Pickup at Low Frequencies +
## 6 Model vs. Real Guitar-String Signal  
To test the validity of the identified Hammerstein model, we set up a different experiment corresponding to a realistic use of the pickup. For that purpose, we use a lab guitar prototype [40]. A guitar string is fixed on an wooden beam. The string is tuned as open low E (\(f_{0}\) = 82 Hz). The pickup under test is set on a mechanical arm on which some precision movement pieces are fixed. Thanks to this system, the pickup position under the string can be adjusted along the three axes. For this experiment, the pickup is set at 1/4 of the total length of the string corresponding approximately to the neck position on a real guitar, and the distance at rest between the string and the pickup is set at 5 mm. A detail of the experiment is shown in Figure 9.  
The string is struck using an impact hammer. A single-point vibrometer (OFV-503 and OFV-505, Polytec, Irvine, CA, USA) pointing at a piece of reflective tape glued to the string and located above the pickup allows the measurement of the string displacement in the vertical plane. Temporal evolution of both string displacement and pickup output voltage are recorded simultaneously and depicted in Figures 10 and 11. A zoom on a few periods of both experimental signals is given for three different time lags along the time-varying response. As expected, the string displacement is distorted just after the excitation (Figure 10--zoom to \(t\) = 1.3 s). It becomes less and less distorted as the harmonics of higher orders fade with time (Figure 10--zoom to \(t\) = 22 s). The output signal of the pickup exhibits the same kind of behavior with time. One can notice that the output voltage is more distorted due to pickup nonlinearities.  
The displacement signal measured with the vibrometer is then used as the input of estimated parametric Hammerstein model of the pickup and both the measured and the synthesized pickup outputs are compared on the same graph (Figure 11). The difference between estimated and experimental signals is plotted on Figure 11, showing that the model succeeds in describing the nonlinear behavior of the pickup when used in realistic conditions.  
Figure 9: Picture of the second experiment in which the pickup is placed under a vibrating string.
## 6 Conclusions  
In this work, an algorithm that estimates the geolocation of a UAV in the absence of a GPS signal was presented. Several factors impact this problem, such as the altitude of the UAV relative to the terrain, the geolocation where the experiment takes place, and the distance of the route. It was demonstrated that there is no way to optimize the scale for pixel-to-meter transformation, so the error will accumulate as the aircraft moves forward. The results show that it is feasible to use satellite image features to extract landmarks that help the UAV estimate its location, even though the images are not updated and have different intensity levels and varying resolutions.  
The algorithm filters the keypoints detected in the satellite image to ensure computational lightness and onboard execution capability to ensure autonomy.  
It is demonstrated that this scheme prevents the error from incrementing over time even in long-range missions.  
Conceptualization, J.G.-A. and C.V.; methodology, C.V.; software, J.G.-A., C.V. and P.M.-R.; validation, N.A.-D.; formal analysis, C.V.; investigation, P.M.-R.; data curation, J.G.-A.; writing--original draft preparation, J.G.-A. and C.V.; writing--review and editing, N.A.-D.; visualization, P.M.-R.; supervision, J.G.-A.; project administration, J.G.-A. and C.V. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the University of Guadalajara through \"Programa de Fortalecimiento de Institutos, Centro y Laboratorios de Investigacion 2024\".  
Not applicable.Not applicable.Not applicable.Not applicable.Data Availability Statement:The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy.Conflicts of Interest:The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of the data; in the writing of the manuscript; or in the decision to publish the results.  
\begin{table}
\begin{tabular}{l c c c c} \hline \hline
**Study** & **Range (m)** & **Altitude (m)** & **Time (s)** & **Error (\%)** \\ \hline Quist [25] & 2400 & NA & 60 & 8.70 \\ [PERSON] and [PERSON] [68] & 500 & 70 & 70 & 8.0 \\ [PERSON] et al. [69] & 1800 & 50 & 160 & 3 \\ [PERSON] et al. [70] & 790 & 5 & 450 & 2.53 \\ [PERSON] et al. [71] & 80 & NA & 450 & 1.3 \\ Our approach & 17,300 & 1200 & 600 & 0.83 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Comparison with other approaches with case studies comparable to ours.
###### Abstract  
Rural areas in Limpopo Province (South Africa) are in urgent need of interventions for safe and secure water supply to adapt to climatic changes and the increased frequency of droughts. A feasibility study was conducted for the adoption of solar-powered groundwater pumping systems and Multiple Water Use Services (MUS) in Greater Giyani Municipality (Limpopo). Stakeholder engagement, geotechnical data and socio-economic information were used in the feasibility study. The Solar Powered Irrigation Systems (SPIS) tool (GIZ and FAO, 2021) was used to design solar-powered shallow groundwater pumping systems at nine case study sites: four villages (water supply for domestic use) and five small-scale farms. Given the technical design configurations, peak water requirements ranged from 28.8 to 58.9 m\({}^{3}\)/d, peak power requirements from 1.2 to 3.4 kWp and required solar panel surface areas from 8.0 to 22.3 m\({}^{2}\). Viable financial mechanisms for the operation and maintenance of MUS are leasing, cooperatives, informal saving groups and pay-per-use. The adoption of the technology appears to be financially and technically viable to augment the water supply. However, groundwater levels will have to be monitored and water purification plants for drinking water will have to be established to ensure long-term sustainability.  
climate change adaptation; community engagement; multiple water use services (MUS); rural water supply; shallow aquifers; solar-powered irrigation systems (SPIS)
## 6 Numerical Simulation Analysis of the Dual-Electrode Excitation Method
### Analysis of Influencing Factors on the Distribution of the Magnetic Induction Intensity Formation
#### 6.4.3 Analysis of Influencing Factors on the Length of Excitation Electrodes  
The combination of electrode length (\(l_{d}\), \(l_{u}\)) is modified for the numerical simulations: (0.2 m, 0.2 m), (0.2 m, 5 m), (0.2 m, 20 m), (20 m, 20 m), and (20 m, 100 m).  
Figure 7a illustrates the impact of different electrode length combinations on the casing current. When the length of the upper/lower electrodes is equal in length, the casing current amplitude presents a symmetrical distribution centered on the ranging point M. As the electrode length increases, there is a significant increase in the casing current amplitude; if the unilateral length of the upper electrode is extended, there is a significant increase in the casing current amplitude on that side. The \(z\) value of the maximum current increases with each combination having the maximum current of 0.14 A, 0.17 A, 0.53 A, 0.65 A, and 0.78 A, respectively. The results show that increasing the electrode length is beneficial to increase the casing current amplitude, and the casing current flows further away. In engineering applications within a water-based mud environment, the optimal combination scheme is found to be (20 m, 100 m). The lower electrode can utilize finite drill tool lengths, while the upper electrode can use drill pipes connected to the ground.  
Figure 7b illustrates the impact of different combinations of electrode length on the induced magnetic field intensity along the axis of the drilling well. The attenuation characteristics of \(B_{c}\) are similar to those of \(I_{c}\). At the measurement position with the upper  
Figure 7: The amplitude of the casing current and the intensities of the induced magnetic field on the axis of the drilling well with different electrode lengths.  
magnetic field (\(z^{\prime}=+2.5\) m), the measured magnetic field intensities are recorded as 0.75 nT, 1.29 nT, 4.05 nT, 4.96 nT, and 6 nT, respectively, for each respective distance of \(L\) mentioned above.
# Developing the Smart Sorting Screw System Based on Deep Learning Approaches
## 3 Experiment and Discussion
### Dataset Descriptions and Experiment Setup  
In this study, the dataset of screw images is captured from the sensing device of the developed optical instrument. The developed system of the optical instrument provides more details, as shown in Figure 4. In order to comprehensively capture the spiral screw, the developed optical instrument is designed to place the screw on the rotating plate, which is perpendicular to the lens. In addition, the stepper motor can drive the rotating plate to rotate in 360 degrees. For each screw product, about 200 images of screw images can be captured in 5 s. Moreover, the image quality is an essential factor, which will affect the result of the subsequent analysis in this study. The screw images are captured on the Hikvision camera coupled with the MORITEX lens, which can generate the high quality of the screw images. To capture the defective region on the screw more clearly, the front light of the light bars are placed on two sides of the object to create strong reflections on the screw surface. The experimental images of the spiral screw are shown in Figure 5, where the defective region on the spiral screw is indicated with the red arrow, and each image has the same scale with 762 \(\times\) 920 pixels. The image resolution is approximately 0.03 mm/pixel.  
Figure 3: The architecture of the autoencoder model.  
Moreover, the convolutional and adversarial autoencoders are used as the core AI models for detecting the defective region on the screw image. In this experiment, both of these two networks are implemented on the cloud platform of NVIDIA GTX 1080 GPU with the TensorFlow framework. The hyper parameters of CAE were set as 8500 epochs, 0.05 learning rate, mean squared error of loss function, and Adam optimizer. The AAE model parameters were set as 10,000 epochs, 0.0002 learning rate, mean squared error and binary cross-entropy of loss function, and Adam optimizer.
# Dynamic Shortest Paths Methods for the Time-Dependent TSP
## 3 A Branch-and-Price Algorithm
### Valid Inequalities
#### 3.4.2 Incompatibilites  
Incompatibilites between binary variables, collected in the so-called incompatibility graph, have proven to be highly useful in order to generate strong inequalities for mixed-integer programs in general (see [35]). For the ATSP, two arcs \((u,v)\
eq(u^{\prime},v^{\prime})\) are incompatible if they share one or both of their endpoints, that is,  
\[u=u^{\prime}\quad\text{ or }\quad v=v^{\prime}\quad\text{ or }\quad\big{(}u=v^{\prime}\,\text{ and }u^{\prime}=v\,\big{)}.\]  
The two common classes of inequalities derived from incompatibility graphs are clique and odd-cycle inequalities. Cliques in the incompatibility graph of the ATSP correspond to the sets \(\delta^{+}(v)\) and \(\delta^{-}(v)\). For the (TDISP-A), clique inequalities are already implied by the constraints.  
Odd-cycle inequalities for the ATSP are known as odd closed alternating trail inequalities [36], odd CATS for short. An odd CAT corresponds to a sequence \(a_{1},\ldots,a_{2k+1}\) of distinct arcs in \(A\) such that arcs \(a_{i}\) and \(a_{i+1}\) share either head or tail. The odd CAT inequality corresponding to these arcs is given by  
\[\sum_{i=1}^{k}y_{a_{i}}\leq k.\]  
Odd CAT inequalities for the ATSP can be separated heuristically by computing shortest paths in an auxiliary bipartite graph. For the TDISP, these cuts correspond to odd cycles of cliques rather than odd cycles of simple incompatibilities.
## 6 Results and Discussion
### Analysis of Throughput  
Different scenarios for the AMCTD protocol's throughput, i.e., without attack, with 4, 8 and 12 attacker nodes, are plotted in Figure 8. According to the data, AMCTD with no attacker nodes has a higher throughput than AMCTD with 4, 8, or 12 attacker nodes. It demonstrates how the AMCTD protocol's throughput performance suffers noticeably from active attack. Significant degradation in terms of throughput has been observed in the attack scenarios.  
The throughput of the AMCTD protocol is described in Figure 9 for various circumstances. According to the findings in Figure 9, the AMCTD protocol's throughput is 41.2% when there is no attack, 35.8% when there are 4 attacker nodes, 40.3% when there are 8 attacker nodes, and 37.8% when there are 12 attacker nodes. Furthermore, it is evident from Figure 9 that an active attack decreases the throughput of the AMCTD protocol by approximately 6%.  
Figure 8: AMCTD: Throughput Analysis without attack and with 4, 8 and 12 Attacker Nodes.  
Figure 9: Throughput of AMCTD without Attack, AMCTD with 4, 8 and 12 Attacker Nodes.