esa-sceva/satcom-chunk-collection huggingface dataset:
# Fully Reconfigurable Photonic Filter for Flexible Payloads
## 5 Conclusions  
Reconfigurable photonic filters have garnered significant attention due to their potential to enhance the functionality of space payloads. These advanced devices harness the properties of propagating light to deliver superior performance in signal processing, filtering, and frequency selection.  
In scenarios where satellite communication frequencies are congested, leading to multiple signals sharing the same spectrum, reconfigurable photonic filters simplify spectrum management and interference mitigation. This, in turn, ensures dependable signal transmission.  
These advantages open doors to various applications in space payloads, including agile frequency channelization, enabling the simultaneous processing and analysis of diverse frequency bands. Through the adaptive suppression of unwanted interference, these filters enhance overall communication performance, simplifying signal processing algorithms. As a result, they improve both signal reception and transmission, allowing for precise and targeted communication with Earth stations and other space assets.  
In this context, we have proposed a fully reconfigurable filter with an impressive stopband rejection of 45 dB. This filter comprises two tunable decoupled ring resonators capable of adjusting both bandwidth and central frequency. Achieving this tuning requires only a small amount of power (ranging from 0 to 11.50 mW), thanks to the efficient thermo-optic tuning of silicon. However, it is worth noting that this tuning process is relatively slow, taking 9.20 \(\upmu\)s.  
Our proposed filter can achieve, theoretically, a bandwidth reconfigurability of 20 MHz by heating one resonator. By feeding electric currents to both ring resonators, we can achieve a maximum central frequency shift of 180 MHz without affecting the bandwidth.  
Conceptualization, A.d.T. and G.B.; methodology, C.C.; software, A.d.T.; formal analysis, A.d.T., G.B., N.S. and C.C.; investigation, A.d.T.; writing--original draft preparation, A.d.T.; writing--review and editing, G.B., N.S. and C.C.; supervision, C.C. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The data presented in this study are available on request from the corresponding author.  
The authors declare no conflicts of interest.
## 2 Concept of Micro-Grid Systems
### Description of the Developed System  
The developed DC microgrid system includes different loads such as a commercial load, industrial load, and residential load. The capacity of the power produced by all DG sources are 150 kW for solar, 150 kW for wind energy, and 345 kWh for battery banks. Power generation from the PV and battery is DC, but for wind, it is AC; therefore, the power generation from the AC source is converted to DC by using a rectifier. To reduce the voltage fluctuation, each DG source is equipped with a converter. A battery is used to ensure power supply to consumers without any interruption. The DC microgrid supplies the loads directly by 380 Vdc. The total produced power, which includes PV and wind, are connected in parallel. The battery bank will be used as back-up power during peak demand and to decrease variations in the power produced by renewable sources. Thus, the total power required to supply the loads is 280 kW. Figure 3 illustrates the block diagram of the developed DC microgrid system.
# Oral and Dental Spectral Image Database--ODSI-DB
###### Abstract  
The most common imaging methods used in dentistry are X-ray imaging and RGB color photography. However, both imaging methods provide only a limited amount of information on the wavelength-dependent optical properties of the hard and soft tissues in the mouth. Spectral imaging, on the other hand, provides significantly more information on the medically relevant dental and oral features (e.g. caries, calculus, and gingivitis). Due to this, we constructed a spectral imaging setup and acquired 316 oral and dental reflectance spectral images, 215 of which are annotated by medical experts, of 30 human test subjects. Spectral images of the subjects' faces and other areas of interest were captured, along with other medically relevant information (e.g., pulse and blood pressure). We collected these oral, dental, and face spectral images, their annotations and metadata into a publicly available database that we describe in this paper. This oral and dental spectral image database (ODSI-DB) provides a vast amount of data that can be used for developing, e.g., pattern recognition and machine vision applications for dentistry.  
spectral image; dentistry; oral; dental; dataset; database +
Footnote †: journal: Medical Image Analysis
## 5 Numerical Simulations
### Simulation Strategy  
To examine the performance of the algorithm at different levels of inconsistencies, we chose two types of random PCMs:  
1. Random matrices from the Saaty scale \(\{1/9,1/8,\ldots,1/2,1,2,\ldots,8,9\}\); and
2. Random consistent matrices on \([1/9,9]\) with a slight modification by multiplicative perturbation using the _log-normal_ distribution (\(\mu=0\), \(\sigma=0.65\)) which leads to inconsistent PCMs with more realistic _CR_ values close to [PERSON]'s threshold \(0.1\). To be more precise, the consistent matrix is modified by multiplicative perturbation \(U\) (Hadamard component-wise multiplication by \(U\) respecting the interval \([1/9,9]\) and then reconstruct the lower triangular matrix through reciprocity), where \(U\) is an upper triangular matrix generated from the _log-normal_ distribution [62] (pp. 131-134).  
Note that type (ii) matrices correspond to more reasonable real-life cases with respect to the very general type (i) matrices.  
In order to construct an incomplete PCM, the procedure of an 'eliminating strategy' in both classes of matrices with matrix size \(n=4,5,6,7,8,9,10\) is given as follows. First, a complete pairwise comparison matrix is generated. Then, we remove one or more entries at random using a uniform distribution in the upper triangular first to produce a various number of missing entries for each matrix size accordingly. Subsequently, we reconstruct the lower triangle starting from the upper one to have the reciprocals of the unknowns. Furthermore, an incomplete PCM will hence be constructed. In all this, there is a test to check whether the graph is connected.  
In the end, a complete PCM is reconstructed on the basis of a connected graph by applying the proposed algorithm with bound constraints on \([1/9,9]\). Furthermore, then the average _CR_ on the 10,000 simulations will be calculated for a fixed number of missing entries (\(k\)) from the given matrix size \(n\) (a similar procedure was applied by [63] (pp. 7-8)). More precisely, the steps for calculating the average CR of the reconstructed matrices on the basis of connected graphs for both matrix types (i) and (ii) are as follows:  
1. Fix \(k\) and \(n\);
2. Generate a random complete PCM on \([1/9,9]\);
3. Make the matrix incomplete at random positions using a uniform distribution;
4. Identify whether the graph associated with an incomplete matrix is connected or disconnected. If it is connected, then we apply the proposed algorithm for the optimal completion of the incomplete PCM using the same interval constraint \([1/9,9]\);
5. Compute and save the CR value for the reconstructed matrix;
6. Repeat steps (2)-(5) until \(10,000\) CR values are obtained;
7. Calculate the average CR.
## 4 Experimental Results and Their Analysis
### The Impact of Longitudinal Reinforcement
One of the main causes of losing the balance by the longitudinal bars is a too small protective concrete layer on the inner part of the annular element. The thickness from 10 mm to 15 mm of the protective layer can hardly ensure sufficient cohesion of longitudinal reinforcement with concrete. For this reason and because of the isotropy of concrete deformability, which is present through the wall's thickness, the cohesion of internal reinforcement with concrete is decreased (weakened). This explains the lack of stability of reinforcing bars under the loads approaching the point of destruction. Figure 5: Coefficients \(\alpha_{s1}\), \(\alpha_{s2}\), \(\alpha_{s3}\), \(\alpha_{s4}\) dependence on (**a,b,c,d**) the ratio of longitudinal reinforcement \(\mu_{s}\) and (**e,f,g,h**) wall thickness t, while the spiral pitch s = 100 mm. Figure 6: Dependence of the modulus of elasticity of non-reinforced, centrifuged concrete, \(E_{c}\), on the concrete strength, \(f_{c}\). According to technical regulations and design manuals [33; 34; 35] when the thickness of the whole element is 500 mm the thickness of the external protective layer should reach at least 15 mm. The thickness of the longitudinal reinforcement protective layer on the inner side is not regulated. However, the cross-section parameters recommended in these regulations for the wall thickness of 50 mm and the external diameter of 300 mm to 500 mm the internal layer of 15 mm is acceptable. The pitch of spiral reinforcement of these elements should be 100 mm, while the cross section of longitudinal bars--10 mm, which corresponds to the parameters of some specimens in a number of the research works performed by the authors. As shown by the presented research, the considered cross section and reinforcement parameters cannot ensure the efficient and safe performance of centrifuged elements and, therefore, the thickness of the protective interior layer should increase. The longitudinal reinforcement strongly affects the formation, compaction and hardening of centrifuged concrete. It negatively affects its structure and physical-mechanical characteristics, decreasing the elasticity modulus of centrifuged concrete more than its compressive strength. The decrease in features depends on the amount of longitudinal reinforcement, its position in the cross section, the thickness of the element's wall, and, as shown in further research by the authors, the grading of a coarse aggregate. Longitudinal reinforcement by high-strength bars actually does not affect longitudinal strains corresponding to centrifuged concrete strength. However, this type of reinforcement greatly increases the number of longitudinal strains of the reinforced, centrifuged concrete elements, matching the element's carrying capacity.
# A Fast Method for Calculation of Marine Gravity Anomaly
## 4 Conclusions  
We proposed a fast method to accelerate the calculation of marine gravity anomalies. In the fast method, we improved the calculation process of the ISF method and used GPU parallel computing technology. We provided the MATLAB code for the fast method and outlined the steps of this code in detail. We demonstrated the accuracy and efficiency of the proposed fast method for the calculation of large-scale data through several tests.  
This proposed fast method is limited by the performance of the GPU cards. If the GPU card has less onboard memory, the proposed method cannot be implemented. Moreover, the accuracy of the result from the proposed method depends largely on the quality and the grid interval of geoid height undulation. The quality of geoid height undulation depends on the qualities of satellite altimetry data and mean sea height, and the grid interval of the geoid height undulation depends on the distribution of satellite orbits. Therefore, before the calculation of the proposed fast method, we should collect satellite altimetry data from numerous satellites with different orbits and the mean sea height with high quality to calculate the geoid height undulation with high quality and a small grid interval.  
Both the IHF method and the IVMF method belong to this kind of integral equation method, and they need to overcome the singularity problem. Therefore, after similar corresponding modification, the scheme used in the proposed fast method can also be applied to accelerate the calculation of these two methods.  
Conceptualization, S.H., X.M. and J.W.; Data curation, S.H.; Investigation, Y.G. and H.T.; Software, Y.F. and Y.G.; Visualization, H.T.; Writing--original draft, Y.F.; Writing--review & editing, X.M. and J.W. All authors have read and agreed to the published version of the manuscript.  
This work was supported by (1) the key technologies of high precision gravity and magnetic detection in deep-water oil and gas exploration (grant number: 2016 YFC0303000); (2) The National Natural Science Foundation of China (grant numbers: 41804099, 41530321, and 41974161); (3) Special Project of China Geological Survey (grant number: DD20191006); and (4) Fundamental Research Funds for the Central Universities (grant number: 2-9-2019-040).  
We thank the EGM2008 model and the official website of MATLAB for providing the file geoidegm2008 grid.mat as a free download.  
The authors declare no conflict of interest.
## 3 Control Techniques
### GA Based PID Controller  
A Genetic Algorithm (GA) is considered as a useful optimization tool to search and optimize several parameters of control systems and scientific problems. As such, this paper uses the GA to optimize the PID controller parameters based on a certain objective function. The important step is to encode the problem into suitable GA chromosomes and then build the population. The previous works recommend 20 to 100 chromosomes in one population. The higher chromosome number gives us a better chance to get the optimal results. However, the execution time is a barrier to increasing the number of chromosomes. So, this work uses 80 chromosomes in each generation [3; 29].  
Each chromosome covers three parameters \(K_{p}\), \(K_{i}\), and \(K_{d}\) with value, bounds varied depend on the objective function used. The initial values of \(K_{p}\), \(K_{i}\), and \(K_{d}\) are determined from the Ziegler-Nichols rule, to get a better result.  
The population in each generation is represented by an \(80\times 4\) matrix as obvious in Equation (3), depends on the number of the chromosome in population.  
\[\left[\begin{array}{cccc}K_{p1}&K_{i1}&K_{d1}&J_{l1}\\ K_{p2}&K_{i2}&K_{d2}&J_{l2}\\..&..&..&..\\..&..&..&..\\ K_{pn}&K_{in}&K_{dn}&J_{ln}\end{array}\right] \tag{3}\]  
Figure 3: The corresponding phase current of the BLDC motor model.  
where n: number of chromosomes.  
Each row is one chromosome that comprises \(K_{p}\), \(K_{i}\), and \(K_{d}\) values then the last column is added to accommodate fitness values (\(J_{t}\)) of corresponding chromosomes [4; 30]. The final values of \(K_{p}\), \(K_{i}\), and \(K_{d}\) are determined by minimizing a certain objective function. Many objective functions may be used for this purpose. In this work, the objective function in Equation (11) is considered [31].
# Orbit Decomposition Method for Rotordynamic Coefficients Identification of Annular Seals
## 5 Results and Discussion
### Rotordynamic Results Comparison Between Two numerical Methods
#### 5.1.1 Fluid-Induced Forces  
For the orbit decomposition method, the steady CFD method is used to calculate the tangential and radial forces of the two decomposed circular orbit models. The calculated tangential and radial forces are listed in Table 3. With the known tangential and radial forces, the time-dependent fluid-induced forces of the initial elliptical orbit model can be obtained according to Equation (15).  
For the transient CFD method, when the convergent solution of fluid-induced forces is obtained, the time-dependent fluid-induced forces during the last period are selected to compare with the orbit decomposition method. Taking the case of \(f=30\) Hz as an example, Figure 12 compares the time-dependent fluid-induced force results between the transient CFD method and the orbit decomposition method. Both methods capture the identical periodicity of the time-dependent fluid-induced forces. The fluid-induced forces can be expressed as a sinusoidal function:  
\[F=A\sin(\Omega\,\,\,t+B) \tag{18}\]  
where \(F\) is the fluid-induced force, \(A\) is the amplitude, and \(B\) is the initial phase.  
For the two methods, the fluid-induced force amplitudes at different whirl frequencies are shown in Figure 13. The force amplitudes obtained with the two methods are very  
Figure 12: Comparison of fluid-induced forces at \(f=30\) Hz.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Frequency**} & \multicolumn{2}{c}{**Forward Circular Orbit Whirl**} & \multicolumn{2}{c}{**Backward Circular Orbit Whirl**} \\ \cline{2-5}  & \(F_{f\!f}\) **(N)** & \(F_{f\!f}\) **(N)** & \(F_{f\!b}\) **(N)** & \(F_{f\!b}\) **(N)** \\ \hline \(30\) Hz & \(-21.177\) & \(-51.649\) & \(-0.577\) & \(-15.813\) \\ \(60\) Hz  
close. The maximum difference is less than 3.1%. With the increase in whirl frequency, the amplitudes of \(F_{x}\) and \(F_{y}\) increase. The initial phases of the fluid-induced forces are listed in Table 4. The initial phases of the orbit decomposition method are in good agreement with those of the transient CFD method. The maximum difference is less than 2%.
# Liquid Crystal-Embedded Hollow Core Fiber Temperature Sensor in Fiber Ring Laser
###### Abstract  
An optical fiber temperature sensor based on Mach-Zehnder interferometer and thermopotic effect of the liquid crystal (LC) in fiber ring laser (FRL) system is proposed and experimentally demonstrated. The LC is infiltrated into the core of hollow core fiber, and the resonant wavelength is more sensitive to temperature variation due to the interaction between the incident light and the cavity infiltrating liquid crystal with high thermal light coefficient. Meanwhile, the FRL system was further used to make the sensor have good performance in the case of high signal-to-noise ratio (\(\sim\)35 dB), narrow half-height width (FWHM = 0.15 nm), and high sensitivity in the temperature range from 20 \({}^{\circ}\)C to 50 \({}^{\circ}\)C, with the maximum sensitivity of 1.318 nm/\({}^{\circ}\)C. As far as we know, in the FRL system, the liquid crystal material has a better temperature sensing performance than the previous fiber. Nevertheless, the system has the advantages of good repeatability, low cost, simple production, small volume, high sensitivity. In marine microbial culture and detection, it is necessary to carry out high sensitivity measurement within a small temperature variation range. This reliable and excellent temperature performance has a potential application prospect.  
liquid crystal; fiber ring laser; fiber temperature sensor +
Footnote †: journal: Applied Sciences
## 5 Conclusions  
The pulse-compression technique was successfully implemented in combination with a linear phased array system to inspect a 60 mm thick CFRP sample with artificial defects. This was achieved through the development of a custom hardware-software platform for signal generation/acquisition, together with the complementary tools for the ultrasonic phased array image reconstruction. A series of ultrasonic tests were carried out with the pulse-compression-based system and with a commercial pulse-echo one, and the results were compared. Both the sector scan and the total focusing method images of the sample were obtained with the two methods.  
The two systems produced very similar results, even though the images obtained with pulse-compression exhibited a better sensitivity for the detection of the deepest defects as well as a better defect shape reconstruction compared to the standard pulse-echo method.  
These preliminary results encourage further improvement to the system and to extend the analysis of the benefits of PuC-PA inspection to more challenging samples with higher attenuation or larger dimensions, where the pulse-echo method cannot assure enough sensitivity to detect deep defects.  
Conceptualization, M.R., S.L., and M.K.R.; methodology of sample realization, H.M. and M.G.; software, formal analysis, and investigation, M.K.R., S.L., and M.R.; writing--original draft preparation, M.K.R. and M.R.; funding acquisition and supervision, M.R., H.M., and M.G. All authors have read and agreed to the published version of the manuscript.  
This research work was funded from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 722134--NDTonAIR.  
Not applicable.  
The data presented in this study are available on request from the corresponding author.  
Figure 13: The plot is a cross-section line through the position of the defects which shows the intensity of the TFM image and highlights the obtained SNR at the defects. (**Top**) Intensity of the defects in the TFM image of the PuC-based system shown in Figure 7. (**Bottom**) Intensity of the defects in the TFM image of the standard, commercial pulse-echo system shown in Figure 8.
## 5 Experimental Setup and Database
### Evaluation Metrics  
The results of the speaker clustering system were evaluated in terms of Cluster Impurity (CI). CI measures the quality of a cluster, _to what extent a cluster contains segments from different speakers_. However, this metric has a trivial solution when there is only one segment per cluster. To deal with this, Speaker Impurity (SI) was measured at the same time. SI measures _to what extent a speaker is distributed among clusters_. There is always a trade-off between these two metrics [45]. CI and SI were plotted against each other in an Impurity Trade-off (IT) curve and an Equal Impurity (EI) point was marked as a working point.  
We evaluated the results for speaker segmentation in terms of False Alarm Rate (FAR) and Miss Detection Rate (MDR), as discussed in Reference [46]. The overall speaker tracking system was evaluated in terms of False Alarm (FA) and Missed Speaker Time (MST). In this case, FA is the percentage of duration (in seconds) that is falsely accepted for a target speaker while MST is the percentage of duration (in seconds) that is falsely rejected for a target speaker.