esa-sceva/satcom-chunk-collection huggingface dataset:
# Dhad--A Children's Handwritten Arabic Characters Dataset for Automated Recognition
## 3 Related Work
### Children's Handwriting Classification  
The classification of children's handwriting has been an active area of research for decades, driven by the need for objective and automated assessment tools. Unlike adult handwriting, which tends towards standardization, children's writing exhibits a wide range of variations due to age, developmental stage, and individual learning styles. Early attempts at automated character recognition (OCR) for children's handwriting often relied on template matching techniques. Pioneering works employed pre-defined templates representing ideal character shapes. An input character would be compared to these templates, with the closest match assigned as the recognized character. However, this approach proved ineffective for children's handwriting due to its inherent lack of conformity [19,20]. However, there are a number of limitations identified in the template matching approaches, particularly for characters with significant variations in form.  
Researchers recognized the limitations of template matching and explored alternative approaches. Utilizing statistical and structural features for character classification has been explored by researchers [21, 22, 23]. This involved analysing features like line endings, crossings, and loops within handwritten characters. While offering more flexibility than rigid templates, these methods still faced limitations. The emergence of deep learning techniques, particularly CNNs, has revolutionized the field. Unlike previous methods, CNNs excel at extracting intricate features from the data. This allows them to effectively capture the natural variations in children's handwriting, leading to more robust and accurate character-level classification. Further advancements in deep learning architectures, such as recurrent neural networks (RNNs), have shown promise in handling the sequential nature of handwriting data.
## 2 Optimization Model  
This study adopts a representative facility layout of an ice sports venue as the architectural model, as developed in prior research [27]. The specific equipment layout is shown in Figure 1 below.  
This study focuses on the spectator stands of an ice sports venue. The climate control system in this area comprises a ventilation system, a radiant heating system, and a dehumidifier. The ventilation unit provides fresh air while also delivering air at a regulated temperature to help maintain thermal comfort in the spectator area. Meanwhile, the radiant heaters assist with space heating, and the independent dehumidification system is responsible for maintaining appropriate humidity levels. To ensure coordinated operation among these subsystems, an optimization model for operational strategy is developed, which intelligently generates control commands based on the current system status to regulate device operation and keep the indoor temperature and humidity within predefined limits.  
The model design comprehensively considers weather conditions, electricity price fluctuations, end-user preferences regarding equipment operation, and spectator schedules. With advancements in weather forecasting technologies and electricity market mechanisms, it is now feasible to obtain high-resolution weather predictions and real-time dynamic pricing data over short time horizons. These external inputs provide anticipatory guidance for system control [28].  
Specifically, outdoor temperature, humidity and end-user preferences serve as boundary conditions for thermal and moisture load calculations, enabling the model to forecast future load variations and proactively adjust equipment scheduling. Time-varying electricity prices are incorporated into the objective function as dynamic cost coefficients, guiding equipment operation toward low-tariff periods to optimize electricity expenditure [29; 30]. By integrating environmental signals with economic incentives, the proposed optimization model not only improves the precision of indoor thermal-humidity regulation but also enhances the overall operational efficiency and economic performance of the system. Figure 2 primarily illustrates the relationship between the proposed optimization model and the existing climate control system.
###### Abstract  
This study aims to investigate the CO\({}_{2}\) sorption capacity of hydrochar, obtained via hydrothermal carbonization (HTC). Silver fir sawdust was used as a model material. The batch runs went at 200 \({}^{\circ}\)C and up to 120 min. The hydrochar was activated with potassium hydroxide impregnation and subsequent thermal treatment (600 \({}^{\circ}\)C, 1 h). CO\({}_{2}\) capture was assayed using a pressure swing adsorption (PSA) process. The morphology and porosity of hydrochar, characterized through Brunauer-Emmett-Teller, Barrett-Joyner-Halenda (BET-BJH) and scanning electron microscopy (SEM) analyses, were reported and the sorbent capacity was compared with traditional sorbents. The hydrochar recovered immediately after the warm-up of the HTC reactor had better performances. The Langmuir equilibrium isotherm fits the experimental data satisfactorily. Selectivity tests performed with a model biogas mixture indicated a possible use of hydrochar for sustainable upgrading of biogas to bio-methane. It is conceivably a new, feasible, and promising option for CO\({}_{2}\) capture with low cost, environmentally friendly materials.  
hydrochar; hydrothermal carbonization; biogas upgrading; CO\({}_{2}\) capture; pressure swing adsorption
###### Abstract  
The continuous innovation of satellite payloads is leading to an increasing demand of data-rate for on-board satellite networks. In particular, modern optical detectors generate and need to transfer data at more than 1 Gbps, a speed that cannot be satisfied with standardized technologies such as SpaceWire. To fill this gap, the European Space Agency (ESA) is supporting the development of a new high-speed link standard, SpaceFibre. SpaceFibre provides a data-rate higher than 6.25 Gbps, together with the possibility to use multiple Virtual Channels running over the same physical link, each one configurable with flexible Quality of Service parameters. These features make a SpaceFibre network very appealing but also complex to set up in order to achieve the desired end-to-end requirements. To help this process, a Simulator for HIgh-speed Network (SHINE) based on the open-source toolkit OMNetT++ has been developed and is presented in this paper. It supports the simulation of SpaceFibre and SpaceWire protocols in order to help both the final steps of the standardization process and the system engineers in the setup and test of new networks. SHINE allows to precisely simulate common network metrics, such as latency and bandwidth usage, and it can be connected to real hardware in a Hardware-in-the-Loop configuration.  
SpaceFibre; SpaceWire; network simulator; on-board satellite networks; OMNeT++
# Minimization of Average Peak Age of Information for Timely Status Updates in Two-Hop IoT Networks
## 2 Related Work  
Since the seminal works [2; 3], extensive research has analyzed AoI through queueing models under various service disciplines, such as first-come-first-served (FCFS) and last-come-first-served (LCFS), with or without preemption [19; 20]. Building on these foundational studies, AoI has attracted significant attention for enabling timely status updates in IoT networks. Comprehensive surveys on recent advances in AoI for IoT networks are available in [21; 22]. In this section, we discuss prior studies relevant to our work, with a focus on three key aspects of AoI reduction in short-packet communications: (i) blocklength optimization, (ii) packet concatenation, and (iii) error control techniques.
# Wind Turbine Gearbox Fault Diagnosis Based on Improved EEMD and Hilbert Square Demodulation
## 3 The Proposed Method
### The Proposed Method  
Typical wind turbine systems have a complex structure and combine many different components. Therefore, the vibration signal measured from wind turbine gearboxes is characteristically nonlinear and non-stationary. The useful fault feature in the vibration is very weak and dominated by strong gear meshing frequencies. The low signal to noise ratio (SNR) and transient nature pose significant difficulties and challenges to fault diagnosis of wind turbine gearboxes. Moreover, gear tooth damage leads to a reduction in gear tooth stiffness intermittently throughout the rotation of the gear. Changes due to the gear damage appear in the vibration spectrum as amplitude modulation. To overcome the above limitation, a fault diagnosis method based on improved EEMD and HSD has been proposed. Firstly, the frequency components of the raw vibration signal were calculated to determine whether a resample was needed. Secondly, the raw vibration signal or resampled signal were decomposed into a series of IMFs using EEMD. Then, the fault-related signal, which had the highest kurtosis value, was selected and processed by HSD. Finally, spectrum analysis was applied on the demodulation signal and a satisfactory extraction result was obtained. The complete process of the proposed approach is shown in Figure 4, which includes the following steps:  
1. Spectrum analysis to extract the distributions of the frequencies of the vibration signal, using the resampling frequency criterion to calculate the resampling frequency value \(f_{r}\).
2. Raw vibration signal resample. Subtract the resampling frequency from the sampling frequency: \[f_{e}=f_{\mathrm{s}}-f_{r}\] (17) If \(f_{e}\geq f_{\mathrm{max}}\), resample the raw vibration signal with resampling frequency \(f_{r}\), and output the resampled signal; otherwise, output the raw vibration signal directly.  
The resampled signal decomposes by means of EEMD. Use EEMD to decompose the vibration signal obtained in Step 2 into a set of IMFs.
* Sensitive IMF selection with the biggest kurtosis index value.
* Feature information extraction from sensitive IMF by HSD. Use HSD to demodulate sensitive IMF to extract feature information from the demodulated signal.
* Fault type identified by means of spectrum analysis.
# Compact High-Diectivity Contra-Directional Coupler
## 4 Discussion  
Most power systems operate in a relatively narrow band (for example, the Ku-band satellite uplink operates at 14-14.5 GHz), because the active power component does not have wideband performance. However, the previous studies on microstrip directional couplers have been mainly focused on increasing their directivity without considering structures that are suitable for high-power applications, or on increasing the bandwidth to be much wider than that of most high-power systems.  
In this paper, we proposed a compact weak coupling high-directivity coupler suitable for high power without any weak structure. In order to achieve this, the design is approached from the general ring-type four-port with an uncompensated parallel-coupled line, not from the parallel-coupled line with a compensation structure vulnerable to high power. Additionally, all derivations of the design are presented.  
The measured results, especially the return loss, could be improved if the connectors are de-embedded with a more complex calibration method, such as four-port TRL calibration. However, the return loss is sufficient for applications, and the results of the proposed coupler show wide enough bandwidth for Ku-band satellite uplink high-power applications, and the most compact size for high power, even with high directivity at weak coupling. The proposed design can be integrated very effectively into the most practical microwave and millimeter-wave power systems.  
[PERSON] conceptualized the proposed idea, conducted the simulation, and wrote the original draft. M.J.C. performed validation, measurement, and data curation. [PERSON] supervised the study. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
**Data Availability Statement:** Not applicable.  
**Conflicts of Interest:** The authors declare no conflict of interest.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Works** & \begin{tabular}{c} **Freq. (20 dB** \\ **dir.)** \\ **(GHz)** \\ \end{tabular} & \begin{tabular}{c} **Size** \\ **(mm)** \\ \end{tabular} & \begin{tabular}{c} **FoM. (S/\(\Lambda\))** \\ **(mm)** \\ \end{tabular} & \begin{tabular}{c} **Cpl.** \\ **(dB)** \\ \end{tabular} & \begin{tabular}{c} **Dir. (min.)** \\ **(dB)** \\ \end{tabular} & \
\begin{tabular}{c} **Dir. (peak)** \\ **(dB)** \\ \end{tabular} &
\begin{tabular}{c} **High-Power** \\ **Structure** \\ \end{tabular} \\ \hline
[9] & 1.2-2.8 \({}^{\star}\) & 18.9 \(\times\) 5.4 & 0.80 & 30 & 20 & 28 & \
\begin{tabular}{c} No (thin \\ interdigital stub) \\ No (thin short \\ stub) \\ No (thin short \\ stub) \\ No (thin short \\ stub) \\ No (thin short \\ stub) \\ Yes Yes \\ Yes \\ Yes \\ No (hard shape) \\ Yes Yes \\ Yes \\ Yes \\ Yes \\ Yes \\ Yes \\ Yes \\ Yes \\ Yes \\ Yes \\ Yes \\ \\ \hline \hline \end{tabular} &
\begin{tabular}{c} 18.9 \(\times\) 5.4 \\ 11.0 \(\times\) 10.3 \\ 53.4 \(\times\) 23.2 \\ 2.50 \(\times\) 18 \(\times\) 17 \\ 52 \(\times\) 8 \(\times\) 13.87 \\ 13.8 \(\times\) 6 \\ 13.74 \(\times\) 16 \\ 13.78 \(\times\) 6 \\ 13.78 \(\times
## 5 Discussion  
Comprehensive analysis, when the cumulative penetration is 10 cm, the number of hammer blows required for the No. 1 pile before grouting is about 12, the No. 2 pile is about 9, and the No. 3 pile is about 12; the number of hammer blows required for the No. 1 pile after grouting is about 17, the No. 2 pile is about 13, and the No. 3 pile is about 12. According to the recommended correction factor for the length of the heavy-duty dynamic penetration rod, the test pile can take a factor of 0.44 [26]. It can be obtained that when the cumulative penetration is 10 cm, the number of hammer blows required for the No. 1 pile before grouting is 5.28, the No. 2 pile is 3.96, and the No. 3 pile is about 5.28; after grouting, the number of hammer blows required for the No. 1 pile is 7.48, the No. 2 pile is 5.72, and the No. 3 pile is about 5.28. According to the data of this test, the characteristic value of the bearing capacity of the foundation soil of the bearing layer is 200 kPa, which corresponds to the characteristic value of the bearing capacity of the gravel foundation when the number of hammer blows is 5 in Table 3, which is the same as the grouting of the three piles in this test [27]. The number of hammer blows before is relatively close, so this table is used to analyze the bearing capacity of the foundation. According to the conversion from the table, the characteristic value of the foundation bearing capacity of the bearing layer of the No. 1 pile before grouting can be obtained as 211.2 kPa, the No. 2 pile is 168.8 kPa, and the No. 3 pile is 211.2 kPa; after grouting, the bearing capacity characteristics of the bearing layer of the No. 1 pile is 299.2 kPa, 228.8 kPa for pile No. 2, and 211.2 kPa for No. 3 pile, which can be seen in Table 4. It can be shown that the foundation bearing capacity of the No. 1 pile before and after grouting increased by 41.7%, and the No. 2 pile increased by 35.5%. The characteristic value of the bearing capacity of the foundation after grouting calculated by this method can also provide reference for similar projects.  
\begin{table}
\begin{tabular}{c c c} \hline \hline \multicolumn{1}{c}{**Characteristic Value of Foundation**} & \multirow{2}{*}{**Before Grouting**} & \multirow{2}{*}{**After Grouting**} \\ \multicolumn{1}{c}{**Bearing Capacity (kPa)**} & & \\ \hline No. 1 pile & 211.2 & 299.2 \\ \hline No. 2 pile & 168.8 & 228.8 \\ \hline No. 3 pile & 211.2 & 211.2 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Characteristic values of foundation bearing capacity before and after grouting.  
From the data of No. 1 and No. 2 piles, the grouting amount increased from 250 kg to 500 kg, and the bearing capacity increased from 35.5% to 41.7%, it shows that when other grouting parameters remain unchanged, increasing the grouting amount can effectively improve the bearing capacity.
## 5 Numerical Simulation Results  
### The Settlement Analysis of Ground Surface  
In order to explore the influence of different curve radii on the surface subsidence, this paper selects four types of shield tunnels as the research objects, namely 100 m, 350 m, 600 m, and straight tunnels, and selects the line between the inner and outer centers of the surface of the curve model in Figure 3 as the monitoring line and records the surface settlement value. The surface settlement curves of different tunnels are shown in Figure 7.  
It can be seen from Figure 7 that the settlement curves of the four types of tunnels are basically the same, and a V-shaped settlement tank is formed on the ground surface, but the settlement of the curved tunnel is not uniform, and the peak settlement appears inside the tunnel centerline, which is mainly due to the process of the curved shield tunnel excavation. It is caused by factors such as over-excavation in the middle and inner side and uneven force. The maximum settlement of a curve radius with 100 m, 350 m, 600 m, and the straight tunnel is 22.50 mm, 20.01 mm, 18.10 mm, and 17.50 mm, respectively. It can be seen that the maximum surface settlement increases with the decrease in the curve radius, which is consistent with the reference [15]. Compared with the straight tunnel, the maximum surface settlement of the three curved tunnels increased by 28.57%, 14.34%, and 3.44%, respectively. At the same time, it can also be found that with the decrease in the curve radius, the distance between the peak settlement point and the tunnel center continues to increase. Similar conclusions can be found in the reference [21]. It can be seen that the over-excavation of the inner side of the curve section by the shield construction of the small radius curve tunnel will aggravate the surface settlement and change the position of the maximum surface settlement.
## 6 Quality Analysis of the Reconstructed Image  
The measures used to determine the quality of the reconstructed image are divided into objective and subjective. The objective measurements are determined using mathematical operations or by the use of measuring devices WB06. The subjective measurements are determined by human judgement.  
For quality analysis of the _EEDC-BSSP_ compression method, four images are used--_horse, beauty, mask, pills_--as can be seen on Figure 13.  
The images have a size of \(257\times 257\) pixels. The images are compressed using JPEG, JPEG 2000, and EEDC-BSSP compression algorithms with five compression ratios (\(0.8\), \(0.4\), \(0.2\), \(0.1\), and \(0.05\) bpp). The images are then decompressed and the reconstructed images are subjected to further analysis.
# A Multi-Degree of Freedom Tuned Mass Damper Design for Vibration Mitigation of a Suspension Bridge
## 5 Experimental Verification
### Vibration Suppression of Bridge with TMDs  
The designed 2 DOFs TMDs are mounted on point \(A\) and point \(B\), which has discussed in Section 4.2. Figure 18 shows a close view of the TMD1 (shown in Figure 12); except the different dimension parameters, the two TMDs have the same configuration and can be tuned in the same way. For damping the target modes, the optimum FRF of these two TMDs exhibits two distinct modes at 4.37 Hz, 10.08 Hz, and 6.21 Hz, 9.47 Hz, respectively, as shown in Figure 17.  
By referring the previous design [27], the damping is introduced by using eddy current damping, where two symmetric powerful magnets are attached on the pedestal below the mass block of the TMD in Figure 19. The damping value can be tuned by manually adjusting the size and number of the magnets. In Figure 19, the replaceable magnets are used to set the translational damping and the rotational damping at the same time. If necessary, another two symmetric magnets which are attached on the pedestal (the position at the red dashed circles in Figure 19) can provide additional damping for the bending mode.  
The experimental results are shown in Figures 20 and 21. The Figure 20 shows the acceleration responses of the deck: (i) without TMD, (ii) when the structure is equipped with two 2 DOFs. The result shows that the 2 DOFs TMD is very effective in vibration damping of the bridge. In order to quantitatively confirm the performance of TMDs, Figure 21 shows the FRFs of the deck: (i) without TMD, (ii) when the structure is equipped with two 2 DOFs TMDs, targeting the mode pairs (2B,1T) and (1B,2T), respectively. One sees that TMD1 can attain 13.8 dB amplitude reduction of the first bending  
Figure 19: Layout of the symmetric magnets.  
Figure 18: Experimental implementation of the 2 DOFs TMDs. The damping is tuned by changing the magnets.  
mode (1B) and 8.8 dB amplitude reduction of the second torsional mode (2T); Meanwhile, a 10.7 dB amplitude reduction of the second bending mode (2B) is observed after using TMD2, and 10 dB amplitude reduction of the first torsional mode (1T).  
The experimental results indicate that the 2 DOFs TMDs which designed under the kinematic constraint theory guidance can target the bending and the torsion modes at the same time. Comparing with the classical TMD, the 2 DOFs TMD not only achieves vibration reduction, but also avoids increasing the load of the bridge. It is worth mentioning that the final frequency ratios are different from the optimized frequency ratios (Table 4). The optimized frequency ratios are the result of theoretical model calculation. However, the error between the theoretical model and the real structure, as well as the machining and calculation errors, may result in the change of the final frequency ratios. But the role of the optimized frequency ratios in the TMD structural parameter design cannot be neglected.