esa-sceva/satcom-chunk-collection huggingface dataset:
# 3D Ear Normalization and Recognition Based on Local Surface Variation
## 4 Experiments
### Ear Recognition
#### 4.2.3 Robustness to Pose Variations  
Large pose variations of the ear, especially in cases where there is an out-of-plane rotation, may introduce self-occlusions and lead to incomplete data. However, in the case of self-occlusions, we have found that the ear areas with large surface variations such as antihelix and helix are relatively intact. The LSV is responsive to the concave and convex areas of the surface. Therefore, the proposed ICP-LSV algorithm utilizing the LSV-weighted distance would be more robust to self-occlusions. We tested our method on the pose variation subset of UND-G to demonstrate the robustness to pose variations.  
All of the 96 images from 24 subjects were divided into four groups according to the four different views (Figure 10c). Then the four groups were viewed as the gallery set and the probe set in turns, and cross matched against each other. The results are presented in Table 2. [PERSON] [11] and [PERSON]'s [17] results are also given in the brackets. The best results are shown in bold. It can be observed that the proposed method is better than other two methods in terms of Rank-1 recognition rate.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Probe/Gallery** & **Straight-On** & **15\({}^{\circ}\) Off** & **30\({}^{\circ}\) Off** & **45\({}^{\circ}\) Off** & **Average** \\ \hline \multirow{2}{*}{Straight-on} & \multirow{2}{*}{-} & **100\%** & **95.8\%** & **87.5\%** & **94.4\%** \\  & & [100\%,100\%] & [87.5\%,87.5\%] & [83.3\%,70.8\%] & [90.3\%,86.1\%] \\ \hline \multirow{2}{*}{15\({}^{\circ}\) off} & **100\%** & \multirow{2}{*}{-} & **100\%** & **91.7\%** & **97.2\%** \\  & [100\%,100\%] & & [100\%,100\%] & [91.7\%,87.5\%] & [97.2\%,95.8\%] \\ \hline \multirow{2}{*}{30\({}^{\circ}\) off} & **100\%** & **100\%** & - & **91.7\%** & **97.2\%** \\  & [91.7\%,87.5\%] & [100\%,100\%] & & [91.7\%,95.8\%] & [94.4\%,94.4\%] \\ \hline \multirow{2}{*}{45\({}^{\circ}\) off} & 83.3\% & **91.7\%** & 95.8\% & \multirow{2}{*}{-} & **90.3\%** \\  & **[87.5\%,79.2\%]** & [87.5\%,87.5\%] & [87.5\%,**100\%**] & & [87.5\%,88.9\%] \\ \hline \multirow{2}{*}{Average} & **94.4\%** & **97.2\%** & **97.2\%** & **90.3\%** & **94.8\%** \\  & [93.1\%,88.9\%] & [95.8\%,95.8\%] & [91.7\%,95.8\%] & [88.9\%,84.7\%] & [92.4\%,91.3\%] \\ \hline \hline \end{tabular}
\end{table}
Table 2: The comparison of the proposed approach with similar approaches on pose variation dataset. The best results have been bolded.  
Figure 10: Examples of correct recognition in the presence of occlusions and pose variations. (**a**) occlusions with earrings; (**b**) occlusions with hair; (**c**) four kinds of pose variations.
# New Generation Compact Linear Accelerator for Low-Current, Low-Energy Multiple Applications
## 2 LINAC 7 Accelerator Component Descriptions  
### Ion Source  
The first component in the accelerator is an off-resonance electron cyclotron resonance (ECR) ion source. It consists of a plasma chamber made from a special length CF 63 vacuum pipe. One end of the tube is closed with a special cap that includes a coaxial RF feedthrough and a 3 mm tube for the gas feed. The other end of the cylinder is partially closed off by the plasma electrode. The ECR magnetic field is provided by a Hallbach-type permanent magnet arrangement of eight bars that generates a field coaxial with the chamber. Both the magnitude of the magnetic field, as well as the chamber dimensions, have been set to correspond to a 3 GHz RF power input. The RF power is supplied to the chamber through a DC break designed to allow RF to be transmitted, while isolating the RF amplifier from the high voltage used for extraction. The chamber is connected to the rest of the system through an alumina isolator. The setup can be seen in Figure 2.  
The extraction optics are supported by a special flange with a high voltage feedthrough on the ground side of the alumina isolator, and consists of a set of three electrodes that act as an Einzel lens. The two electrodes on the ends are connected to the ground, while the central electrode is connected to a resistive divider that always keeps it at half of the extraction voltage, avoiding the need for an extra high voltage supply. The proton optics are shown in Figure 3. This was set up in this way to minimize the cost of the ion source by having no instruments that require power or communications at high voltage. The ion source is designed to produce 30 keV protons.  
Figure 1: Simplified schematic of LINAC 7.
## 5 Numerical Analysis
### Scenario D--Analysis of Routing Strategies Variation  
This section analyses the results of experimenting with distinct routing strategies with different arrival rates observing the MRT. The adopted routing strategies are provided by the simulation tool JMT [39]. The used strategies are summarized as follows:  
* **Random**: Jobs are directed to one of the stations related to the considered station in output at random. The outbound connections are chosen with the same probability as the inbound links. Each output link in a model with three output connections has a chance of \(1/3\).
* **Probabilities**: Each outbound link's routing probability must be determined. The total number of probabilities must equal one. The 50/50 balance is used in this experiment.
* **Round Robin**: According to a circular routing, jobs are cyclically sent to the outgoing connections.
* **Least Utilization**: At the moment of routing, the destination station is picked as the one with the least amount of traffic.
* **Join the Shortest Queue (JSQ)**: (sometimes referred to as Shortest Queue Length) At the moment the job leaves the routing station, each work is routed to the station connected in output that has the fewest number of jobs in the queue or service.
* **Shortest Response time**: When work leaves the routing station, it is dispatched to the station with the shortest response time for the job's class.  
Figure 7 shows the calculated MRT mean to the six routing strategies considering three arrival rates (\(0.1\,\mathrm{j}/\mathrm{ms}\), \(0.5\,\mathrm{j}/\mathrm{ms}\), and \(1.0\,\mathrm{j}/\mathrm{ms}\)). Let us focus on the highest and lowest MRTs. The highest MRTs were reached with the shortest response time in all three arrival rates. Since the cloud's service time and the fog and respective transmission times are not so different, such instantaneous calculated shortest response time might be highly sensitive. The lowest MRT was obtained with two routing strategies depending on the arrival rate. The routing strategy \"probabilities\" was more efficient with the lowest (\(0.1\,\mathrm{j}/\mathrm{ms}\)) and the highest (\(1.0\,\mathrm{j}/\mathrm{ms}\)) arrival rates. Therefore, considering similar parameters as this study, the system designer should consider using such a routing strategy with extreme workloads (low and high). The arrival rate of \(0.5\) has obtained a different result, in which the random routing strategy has been spotlighted among the others.
# Image Reconstruction Using Autofocus in Single-Lens System
## 2 Methodology
### Clarity Evaluation Function  
Clarity can be used as the standard of image evaluation [34]. The clarity evaluation index produces an extreme value (maximum or minimum value) only for the focused plane in an imaging system [30; 33]. In this section, CEFs are utilized to evaluate the object distance \(z_{1}\). We apply different auto-focusing criterias to estimate the position of a retrieved sample as CEF. The expressions are written as follows [23; 35; 36],  
\[\text{GRA}(z)=\iint\mid\
abla I(z)\mid\text{d}x\text{d}y, \tag{1}\]  
\[\text{LAP}(z)=\iint\Bigl{[}\
abla^{2}I(z)\Bigr{]}^{2}\text{d}x\text{d}y, \tag{2}\]  
\[\text{SG}(z)=\iint\bigl{[}\
abla I(z)\bigr{]}^{2}\,\text{d}x\text{d}y \tag{3}\]  
\[\text{SPEC}(z)=\iint\ln\{1+|\mathcal{F}[I(z)-\bar{I}(z)]|\}\text{d}x\text{d}y, \tag{4}\]  
\[\text{TOG}(z)=\sqrt{\text{std}(|\
abla i(z)|)/\text{mean}(|\
abla i(z)|)}, \;\;\;i(z)=\sqrt{I(z)}, \tag{5}\]  
\[\text{Brenner}(z)=\sum_{x}\sum_{y}[I(x+2,y,z)-I(x,y,z)]^{2}, \tag{6}\]  
\[\text{Entropy}(z)=-\sum_{i=0}^{L-1}p_{i}\ln(p_{i}), \tag{7}\]  
\[\text{VAR}(z)=\sum_{x}\sum_{y}|I(z)-\bar{I}(z)|^{2}, \tag{8}\]  
\[\text{AM}(z)=\frac{1}{\text{M}N}\sum|I(x,y,z)|, \tag{9}\]  
Figure 2: The flowchart of autofocus and image reconstruction in single-lens CDI.  
where \(\
abla\) is the gradient operator. \(|\cdot|\) is the modulus operator. The functions'std' and'mean' are the standard deviation and mean calculation. CEF is regarded as auto-focusing metrics by searching its maximum or minimum. In this paper, instead of creating new CEFs, we combine speckle illumination with CEFs to make existing auto-focusing algorithms more stable and robust. Since the speckle illumination mode makes a re-distribution of gradient data on recording planes.
### CANYVAL-C Mission  
The CANYVAL project (CubeSat Astronomy by NASA and Yonsei using Virtual ALignment) was developed by Yonsei University and NASA and has the ultimate goal of demonstrating a VT by operating 1U and 2U CubeSats in low-Earth orbit. CANYVAL-X, the first phase of the project, was designed to implement the IAH technology experiment by constructing a VT configuration with a variable focal length [33; 34]. As an advanced mission, CANYVAL-C aligns dual satellites at a fixed nominal distance such that the portrait of the corona is valid for executing a scientific mission [35].
## 2 Historical Data
### Aerial Photography in the Polar Regions
Image-enhancement tools in modern photogrammetry software can maximize the extraction of subtle surface features from scanned analogue aerial photographs.
# Remote Sensing Multimodal Image Matching Based on Structure Feature and Learnable Matching Network
## 3 Template Matching Based on PCA-LMN  
The proposed matching algorithm is a full-search template-matching method that compares the template with a candidate window of the same size on the base image to identify the position of the target window (Figure 2). Since the method only searches in translation, a preliminary correction must be performed before the matching, so the direction and scale of the template and the direction and scale of the base image are approximately the same. Usually, the preliminary correction can be automatically performed according to the altitude and attitude information provided by the onboard navigation system [38].  
The template-matching algorithm based on the PCA-LMN consists of three main steps: log-Gabor orientation estimation, orientation enhancement using the PCA, and similarity measurement and translation estimation based on the LMN; the algorithm flowchart is shown in Figure 3.
## 4 Simulation and Experimental Results
### Voltage-Mode Quadrature Sinusoidal Oscillator  
The proposed oscillator was simulated using OrCAD PSpice, and measured using the Agilent N9000A CXA signal analyzer. The supply voltages were V\({}_{\mathrm{DD}}\) = \(-\)V\({}_{\mathrm{SS}}\) = 6 V. The passive components were chosen as C\({}_{1}\) = C\({}_{2}\) = 1 nF and R\({}_{1}\) = R\({}_{2}\) = R\({}_{3}\) = 4 k\(\Omega\). R\({}_{4}\) was adjusted to 3.98 k\(\Omega\) to start the oscillations. The theoretical oscillation frequency using this design was 39.79 kHz. The steady state waveforms for both the quadrature voltages are shown in Figure 27. Figure 28 shows the quadrature relationship between the generated waveforms of V\({}_{\mathrm{o1}}\) and V\({}_{\mathrm{o3}}\) in the X-Y plane. From the simulation results, the oscillation frequency of f\({}_{\mathrm{o}}\) = 38.84 kHz was obtained, which agrees very well with the theoretical analysis The results of the V\({}_{\mathrm{o1}}\) total harmonic distortion analysis are summarized in Table 3.  
Figure 28: Simulated quadrature output waves V\({}_{\mathrm{o1}}\) and V\({}_{\mathrm{o3}}\) in the X–Y plane of Figure 27.  
Figure 27: Simulated quadrature output waves V\({}_{\mathrm{o1}}\) (blue) and V\({}_{\mathrm{o3}}\) (red) of Figure 4.  
Regarding the experimental tests for the proposed oscillator, Figure 29 represents the oscilloscope output waveforms, V\({}_{\rm o1}\) and V\({}_{\rm o3}\), of the proposed oscillator in Figure 4. This is designed for the oscillation frequency of f\({}_{\rm o}\) = 39.79 kHz with the component values of C\({}_{1}\) = C\({}_{2}\) = 1 nF and R\({}_{1}\) = R\({}_{2}\) = R\({}_{3}\) = 4 k\(\Omega\), and the oscillation starts from R\({}_{4}\) = 3.77 k\(\Omega\). The measured oscillation frequency, 38.55 kHz, is very close to theoretical value and the error is \(-\)3.12%. Figure 30 shows the Lissajous pattern of the V\({}_{\rm o1}\) and V\({}_{\rm o3}\) outputs of the experimental result in Figure 29. Figure 31 shows the frequency spectrum of the voltage output, V\({}_{\rm o1}\), of the oscillator. The magnitude of the second harmonic is 38.87 dB less than the magnitude of the fundamental harmonic. The measured oscillation frequency, 37.072 kHz, is close to the theoretical value. Obviously, the experimental results are consistent with the theoretical values. Figure 32 shows how phase noise was calculated using the Agilent phase noise measurement solution. The phase noise in the proposed oscillator is lower than \(-\)85.7 dBc/Hz (at 1 kHz offset). Obviously, the experimental results are consistent with the theoretical values.  
\begin{table}
\begin{tabular}{c c c c c c} \hline
**Harmonic** & **Frequency** & **Fourier** & **Normalized** & **Phase** & **Normalized** \\
**Number** & **(Hz)** & **Component** & **Component** & **(Degree)** & **Phase (Degree)** \\ \hline
1 & \(3.98\times 10^{4}\) & \(8.94\times 10^{-1}\) & 1.00 & \(7.94\times 10^{1}\) & 0 \\
2 & \(7.96\times 10^{4}\) & \(1.45\times 10^{-2}\) & \(1.62\times 10^{-2}\) & \(6.74\times 10^{1}\) & \(-9.14\times 10^{1}\) \\
3 & \(1.19\times 10^{5}\) &
## 4 Results and Discussion
### Maintenance Strategy Based on AE  
Based on the above research and analysis, this study presents a piston rod maintenance strategy based on AE signals. From a qualitative perspective, the criteria for identifying significant damage in the piston rod include a notable increase in the counts, energy, peak-to-peak, and impulse factor of the AE data. This increase signals an escalation of the fatigue damage within the material, leading to the formation of an alarming hazardous condition. Quantitatively, the crack propagation rate model based on the AE energy proposed here facilitates the calculation of the remaining life in a state where initial cracks are known. However, in real-world engineering scenarios, there may be the randomness of monitoring moments and the potential absence of initial crack parameters. Consequently, quantitative calculations can determine the crack propagation within any given time interval, allowing comparison with the critical fracture size of the material to determine the need for immediate shutdown. In conclusion, the AE-based method outlined in this paper serves as a valuable approach to identifying crack damage and assessing the rate of growth of cracks in piston rods. It provides a practical strategy for both qualitative damage identification and the quantitative assessment of crack propagation, thereby serving as an effective tool for diagnosing compressor failures and facilitating predictive maintenance in UGS facilities.
## 5 Conclusions  
In this paper, we use a statistical downscaling of data from seven GCMs, then SVM was used to stimulate and predict the future climate of the North China Plain under various climate scenarios using a multi-GCM model ensemble, analyze its spatial and temporal variability characteristics, and provide the necessary database for future climate adaptation and response to climate change.  
1. The simulated values of extreme temperature indices from the multi-climate model SVM method better agree with the observed values than individual GCM models. The arithmetic means method is suitable for simulating and predicting extreme temperature indices in the North China Plain.  
2. The extreme high temperature indices (TXx, TNx, TXn, TNn, TN90p, TX90p, and SU) indicate a considerable growing tendency for the four future climate scenarios (2061-2100), whereas the extreme low temperature indices drop dramatically. TXx, TNx, TN90p, and TX90p altered the most in the SSP585 climate scenario, whereas TXx, TNx, TN90p, and TX90p changed the least with the SSP126 climate scenario. Under different climate scenarios, TXn, TNn, and Su did not alter appreciably.
3. In the North China Plain, there are significant spatial differences in extreme temperature indices in both historical and future periods, except DTR. The variance in the extreme temperature index grows with the growth of the scenario's radiative forcing, and spatial differences become more pronounced, reaching a maximum under the SSP585 climate scenario.  
Conceptualization, H.W. and D.X.; methodology, H.W. and L.C.; software, H.W.; validation, L.W., G.Y. and H.B.; writing--original draft preparation, H.W.; writing--review and editing, Y.Z., H.B., M.J. and X.X.; visualization, L.W., G.Y., D.X. and J.Y. All authors have read and agreed to the published version of the manuscript.  
This research was supported by the Hebei Provincial Science Foundation for Distinguished Young Scholars (No. D2022205010), the Natural Science Foundation of China (No. 41901128) and Key R & D project of Hebei Academy of Sciences (No. 22102).  
We sincerely thank the editor and anonymous reviewers for constructive comments and suggestions.  
The authors declare no conflict of interest.
# Reduction of Dust on Solar Panels through Unipolar Electrostatic Traveling Wave
## 5 Conclusions  
This study presents a low-cost and efficient electrostatic cleaning system that reduces the effect of dust on the output power of PV panels. It can reduce the consumption of water in solar power plants, at a time when water is becoming scarce.  
The study develops a novel system that provides a multi-channel output waveform to the electrode panel. The design of the electrode panel has no effect on the amount of radiation reaching the PV panel but is effective at removing dust. The geometry of the electrodes has been changed from simple straight lines to create a distribution in the electric field that increases the force exerted on the dust particles and thus efficiency.  
Experiments conducted with a single channel demonstrated the M1 and M2 models provide greater accumulation of dust particles than the M3 and M4 models. However M3 and M4 models are presented as a new design that is effective at gathering particle samples, and may be useful for extraterrestrial applications.  
Although the electric field of electrodes with simple geometry, such as M1 and M2, and thus uniform electric field can be estimated, it is difficult to determine the motion of the particles and cleaning performance, either analytically or numerically, due to the complexity of the equations [30,38]. However, in terms of cleaning performance, parallel and inclined electrodes showed high efficiency in dust cleaning in the four-channel operating condition.  
Conceptualization, S.A. and M.A.; methodology, S.A. and M.A.; software, S.A. validation, M.A., formal analysis, M.A.; investigation, M.A.; resources, S.A.; data curation, M.A.; writing--original draft preparation, S.A. and M.A.; writing--review and editing, S.A.; visualization, S.A.; supervision, S.A.; project administration, S.A.; funding acquisition, S.A. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
This study was produced from the master's thesis prepared by the first author under the supervision of the second author. The software was obtained from the Harran University under Research Project (project no: 18060).  
No conflict of interest.
## 2 Materials and Methods
### Research Design  
This study was conducted using a cross-sectional research design. The data collection process was initiated following the approval of the Duzce University Ethics Committee (Approval No: 138, dated 25 April 2024). In the first session, the purpose and scope of the study were explained to the participants in detail, and informed consent forms were signed. In the second session, anthropometric measurements were taken, including height and body weight, and Body Mass Index (BMI) values were calculated. Additionally, calendar age (chronological age) and sport age (the duration of regular participation in sports) were recorded. In the third session, motor performance assessments were conducted, including a 30 m sprint speed test, vertical jump test, and agility test. All measurements were carried out on the same day. Height, body weight, BMI, calendar age, and sport age data were collected in the morning (between 09:00 and 09:30), while motor performance tests were performed in the afternoon (between 14:00 and 15:00). The performance tests were administered in the following order: 30 m sprint speed, vertical jump, and agility test, with a five-minute rest period between each test. During the measurements, appropriate rest and preparation conditions were provided to ensure optimal physical performance of the participants. The flow of the research process is presented in Figure 1.  
\begin{table}
\begin{tabular}{l c c c c c} \hline \hline
**Variables** & **n** & **Minimum** & **Maximum** & **Mean** &
\begin{tabular}{c} **Std.** \\ **Deviation** \\ \end{tabular} \\ \hline Age (years) & 29 & 17.00 & 32.00 & 19.5172 & 3.05451 \\ Training Age (years) & 29 & 5.00 & 22.00 & 9.5517 & 3.14627 \\ Height (cm) & 29 & 176.00 & 198.00 & 185.0000 & 5.74456 \\ Body Weight (kg) & 29 & 60.30 & 104.70 & 79.4900 & 10.2300 \\ BMI (kg/m\({}^{2}\)) & 29 & 18.41 & 31.29 & 23.19 & 2.476 \\ Vertical Jump (cm) & 29 & 22.67 & 45.63 & 33.8428 & 6.28836 \\ Agility (s) & 29 & 8.95 & 11.05 & 9.9703 & 0.39460 \\
30-Meter Sprint & 29 & 4.08 & 4.68 & 4.3617 & 0.16222 \\ Time (s) & & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Descriptive characteristics of participants.
# Low-Cost IoT Air Quality Monitoring Station Using Cloud Platform and Blockchain Technology
## 3 Methodology
### Sensors
#### 3.1.2 MQ-7  
The MQ-7 sensor is harnessed to detect carbon monoxide, a primary culprit behind air pollution and the onset of various life-threatening diseases. The MQ-7 is a semiconductor sensor specifically designed for the identification of carbon monoxide (CO). Its sensitive material, SnO\({}_{2}\), exhibits lower conductivity in clean air. The sensor is incredibly user-friendly and thoughtfully engineered for accurately detecting CO levels in the atmosphere. It is capable of sensing CO concentrations ranging from 20 to 2000 ppm and is also cost-effective [17]. The sensor is shown in Figure 4.
# Using Satellite-Derived Vegetation Products to Evaluate LDAS-Monde over the Euro-Mediterranean Area
## 1 Introduction
The goal of this paper is to evaluate LDAS-Monde using the evaporation and GPP products for the 2007-2015 period and to assess for the first time the ability of the GOME-2 SIF observations to be an additional independent source of validation of the modeled GPP before and after the joint assimilation of SSM and LAI products in LDAS-Monde. Section 2 is dedicated to the presentation of the model, the data assimilation system and the satellite products. Section 3 shows the impact of the assimilation on the assimilated variables, and the SIF-GPP relationship is investigated. Finally, subgrid variability issues are discussed in Section 4, together with prospects for assimilating new products.