esa-sceva/satcom-chunk-collection huggingface dataset:
# Polarization-Discriminated RSOA-EAM for Colorless Transmitter in WDM-PON
###### Abstract  
The integrated reflective semiconductor optical amplifier (RSOA) and electro-absorption modulator (EAM) is viewed as an appealing solution to the colorless transmitter on the optical network unit (ONU) side of wavelength-division multiplexed (WDM) passive optical networks (PONs), for its broad modulation bandwidth and high optical gain. However, the conventional RSOA-EAM usually exhibits a poor upstream signal eye-diagram because it can hardly simultaneously saturate the downstream signal and boost the upstream signal as required. By exploiting the polarization-depended RSOA gain, we propose a polarization-discriminated RSOA-EAM to improve the quality of the upstream signal eye-diagram. In this device, the transverse electric polarized downstream signal is saturated by the high gain in the RSOA active region made of compressively strained multiple quantum wells, whereas the upstream signal is linearly amplified after polarization rotation. We find that, as the quality of the upstream signal eye-diagram improves with an increased polarization rotation angle, its power drops, which indicates that there exists an optimized rotation angle to reach a compromise between the upstream signal integrity and power. Simulation results show that the dynamic extinction ratio and output power of the upstream signal can reach 8.3 dB and 11 dBm, respectively, through the proposed device with its rotation angle set at an optimum value (80\({}^{\circ}\)), which exceeds the specification (6 dB and 4 dBm) of the upstream transmitter as required by the next-generation PON stage two. The quality of the upstream signal eye-diagram measured in Q-factor is improved by 10 dB compared to the conventional RSOA-EAM design without polarization rotation introduced.  
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## 5 Technique Comparison  
Regression techniques play a vital role in modeling and predicting the performance of SPVSs by analyzing the relationships between various environmental factors, such as solar irradiance, temperature, and humidity, and their impact on energy generation. Four widely used regression methods--LR, LAR, RR, and ENR--offer different approaches for managing high-dimensional data, multicollinearity, and overfitting, which are often encountered in SPVS datasets.  
While machine learning methods, such as ANNs, can offer powerful capabilities for modeling complex, non-linear relationships, the regression methods used in this study--specifically LAR and Elastic Net--offer several advantages. One of the primary benefits of regression methods is their simplicity and interpretability, allowing for easy identification of key factors influencing SPVS performance, such as temperature (X2) and Relative Humidity (X5). Unlike ANNs, which often operate as \"black boxes\", regression models provide transparent coefficients that can be directly linked to physical parameters, which makes them more suitable for applications where interpretability is critical.  
Furthermore, regression models are computationally less demanding than ANNs, requiring fewer resources and training time, which is particularly advantageous in real-time prediction scenarios or when computational resources are limited. While ANNs can capture highly complex relationships and interactions between variables, the linear nature of regression models can still deliver accurate predictions for systems like SPVS monitoring, where relationships between variables are often more straightforward. Thus, regression methods, with their ease of use and computational efficiency, offer a more accessible approach for practical applications in SPVSs.
## 6 Open Challenges, Future Prospects and Research Directions
### Optimized Aperture Designs  
One promising direction is the optimization of aperture designs. By refining the size, shape, and configuration of optical apertures, researchers can further reduce the impacts of turbulence and enhance the quality of the received signal. In this regard, they can identify designs that minimize the scattering and diffraction of optical signals as they travel through the atmosphere. Optimized aperture designs can effectively average out the scintillations caused by atmospheric variations, leading to more stable and reliable communication links. This can involve the use of novel materials and engineering approaches to create apertures that are more efficient and effective in mitigating turbulence.
# Performance Monitoring of Hybrid All-Optical Fiber/FSO Communication Systems
## 3 Results and Discussions  
In this section, we utilize two metrics to evaluate the performance of the proposed model in predicting the various values of the channel parameters. The metrics are the Coefficient of Determination (R-squared) metric and the RMSE metric. The R-squared metric is given mathematically by  
\[\rho=1-\frac{\sum_{n=1}^{N}(m_{n}-\hat{m}_{n})^{2}}{\sum_{n=1}^{N}(m_{n}-\bar{ m})^{2}}. \tag{3}\]  
The R-squared metric utilizes the actual and estimated data, sample mean (\(\bar{m}\)), and the total number of test samples (\(N\)), with \(m_{n}\) and \(\hat{m}_{n}\) representing the actual and estimated data, respectively. The metric's range is between 0 and 1, with higher values indicating improved prediction accuracy as \(\rho\) approaches 1. Conversely, the prediction accuracy deteriorates as \(\rho\) approaches 0. On the other hand, the RMSE metric is defined mathematically by  
\[RMSE=\sqrt{\frac{1}{N}\sum_{n=1}^{N}(m_{n}-\hat{m}_{n})^{2}}. \tag{4}\]  
In addition, we use a visualization method, the boxplot method, to examine the proposed model's performance. It is a graphical tool used to display the distribution of a dataset. It is constructed from five key statistics: the minimum and maximum values, the lower and upper quartiles, and the median. The box in the plot represents the interquartile range (IQR), which is the range between the first (25 th percentile) and third (75 th percentile) quartiles. The median is represented by a line inside the box. The whiskers extend from the box to the minimum and maximum values that lie within a certain distance from the box, typically 1.5 times the IQR. Any points outside this range are considered outliers and are represented as individual points. Boxplots are used to visualize the spread and skewness of data and to compare multiple datasets side-by-side. The boxplots in Figure 3 illustrate the prediction accuracy of the model under different channel types. High-accurate predictions are represented by narrow boxes.  
Subsequently, we present the results of monitoring each parameter, taking into account the prediction of each parameter under different conditions: when there are no other impairments (single impairment: ASE, CD, turbulence), when there is a joint impairment (double impairment: ASE and CD, ASE and turbulence, CD and turbulence), and when all the impairments are present (triple impairment: ASE, CD, turbulence). It is worth noting that we considered the severe impairment conditions in evaluating the model performance defined by 12 dB OSNR, 500 ps/nm CD, and \(10^{-15}\) m\({}^{-2/3}\) turbulence. Moderate and light conditions will result in much better prediction accuracy.
# Multi-Wavelength Quantum Key Distribution Emulation with Physical Unclonable Function
## 5 Preliminary Results and Validation of QKD Emulation with PUF
### PUF Error  
The previous sections showed the sample error from test keys (75 trits in length) and describe the error of the emulation system, isolated from the PUF. To observe error introduced by the PUF to the emulation system we can look at longer test keys. PUF error results from variations in the real-time client device measurements that cause the measurement to be different from the stored measurements on the server. These client devices are described in Section 4.3.  
To check for PUF error, we generated 3825 trits using the ternary protocol in Section 2.22 and compared the client and server PUF ternary messages to identify errors introduced by the PUF. Out of the 3825 trits transmitted using the PUF, only 10 of those trits were erroneous, in that the input-output did not match, despite the bases matching. This means that in the unobscuring process, described in Sections 2.2.2 and 2.2.3, the client PUF message did not match the server PUF message, resulting in a different output trit when unobscured.  
Our results showed a total of 10 errors from the PUF for the 3825 test trits, which is an error rate of about 0.26%. These initial results are promising and show relatively low error introduced by the PUF.
## 2 Study Area and Data  
### Study Area  
The study was conducted in Wuhan (113 deg41'E-115 deg05'E, 29 deg50'N-31 deg22'N), the capital of Hubei Province, located in central China and covering an area of 8494.41 km2 (Figure 1). Wuhan has a humid subtropical climate, with an annual total precipitation of 1315 mm and an annual mean temperature of 17.13 \({}^{\circ}\)C. Wuhan has a wealth of water and forest resources. It lies at the intersection of the Yangtze and Han rivers, and contains 166 lakes and over 70 parks. Its natural vegetation is composed primarily of deciduous broadleaf trees and evergreen broadleaf trees, such as camphor and oak. Evergreen needleleaf trees (e.g., _Pinus massoniana_ Lamb) are also common in Wuhan, but they are sparsely mixed with broadleaf trees.  
Wuhan is among the fastest growing cities in China, and has experienced rapid urban expansions in recent decades. The urban area in Wuhan increased from 4.19 \(\times\) 10\({}^{4}\) ha in 1988 to 49.39 \(\times\) 10\({}^{4}\) ha in 2011 [28], and the urban landscape became more fragmented. Wuhan comprises 13 districts with a total population of approximately 10.4 million. Our study area includes 11 districts, covering the whole metropolitan area and within one tile of Landsat images.
# Energy-Aware Security Adaptation for Low-Power IoT Applications
## 4 Dynamic Security and Energy Adaptation
### Analytical Evaluation in the Context of LoRaWAN
#### 5.2.1 Configuration of the Test Scenarios  
To carry out this analytical evaluation, it was necessary to define the scenarios to be tested, their initial configurations and the logic implemented in each evaluation. We tested two different scenarios: the first where no attacks on the system are recorded, and another where there are constant attacks against communications, each with a high impact of 80%. The preferential factor, which represents the importance attributed to battery savings by the application, was tested with values of 80% (which gives priority to battery savings over security) and 20% (the opposite scenario), and the minimum level of security for levels 1 and 2. The size of each message is 51 Bytes, the maximum payload size used for LoRaWAN configurations where SF is 12. The transmission rate considered is of one message every half a minute. The battery characteristics are also maintained, considering the same type of battery (with 9720 Joules available) and applicable discharge curve.  
The value of the transmission energy cost is of 0.59 mJ per bit [19] and equals a total of 6.136 mJ, for values measured for a LoRa SX1272 transmitter, which is common in IoT sensors as those employed in LoRaWAN environments. The values used for the energy cost of security are the same as those used in the previous tests, illustrated in Table 5. In this evaluation, the scenario in which the security of the system does not change was also analyzed, and in this case, we chose the fourth security scheme from Table 5, with the objective of comparing the remaining results with the currently most common usage scenario of security in a LoRaWAN network. Please note that the preference threshold and minimum security level settings are not applicable here, as these variables are only used by the Controller.
# Research Progress in the Construction and Application of In Vitro Vascular Models
## 2 Construction of In Vitro Vascular Models
### Construction of In Vitro Vascular Model Based on Microfluidic Technology
#### 2.1.1 Photolithography and Soft Lithography
Increasing the hydrophilicity of the PDMS surface is conducive to the attachment of biomaterials and cells, which can make microfluidic technology more widely used in the construction of vascular models. \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multicolumn{2}{c}{**PDMS Surface**} & \multicolumn{1}{c}{**Principle**} & \multicolumn{1}{c}{**Advantages**} & \multicolumn{1}{c}{**Disadvantages**} \\ \hline \hline \multirow{4}{*}{\begin{tabular}{c} Surface \\ activation \\ modification \\ \end{tabular} } & Gas plasma & \multirow{4}{*}{\begin{tabular}{c} \\ \end{tabular} } & Short processing time & \multirow{4}{*}{\begin{tabular}{c} \\ and simple \\ operation. \\ \end{tabular} } & Longer processing time, & \multirow{4}{*}{\begin{tabular}{c} \\ and the surface \\ hydrophilicity \\ may decrease or even \\ disappear over time. \\ \end{tabular} } \\ \cline{2-2}  & \begin{tabular}{c} \(\mathrm{UV}/\mathrm{ozone}\) \\ treatment \\ \end{tabular} & & & \begin{tabular}{c} \(\mathrm{Deeper surface}\) \\ modification; mild process; \\ lower cost. \\ \end{tabular} \\ \hline \hline \multirow{4}{*}{\begin{tabular}{c} Physical \\ adsorption \\ \end{tabular} } & Protein coating & \multirow{4}{*}{\begin{tabular}{c} Coating the PDMS surface with \\ extracellular matrix proteins \\ to increase \\ hydrophilicity. \\ \end{tabular} } & Simple, fast, and & \multirow{4}{*}{\begin{tabular}{c} Poor stability makes it \\ effective. \\ \end{tabular} } \\ \cline{3-3}  & & & \begin{tabular}{c} Utilizing the \\ reaction between \\ alkoxy groups \\ and PDMS \\ substrate to \\ generate Si-C-Si \\ covalent bonds, \\ in order to \\ introduction \\ hydroxyl1 groups, amino groups, \\ thiol groups, or \\ carboxyl groups. \\ \end{tabular} & \begin{tabular}{c} Utilizing the \\ reaction between \\ alkoxy groups \\ substrate to \\ covalent bonds, \\ reproductibility, with the \\ surface \\ parameters of \\ the polymerization \\ process. \\ \end{tabular} \\ \hline \hline \multirow{4}{*}{\begin{tabular}{c} Polymer surface grafting \\ \end{tabular} } & \multicolumn{1}{c}{\
\begin{tabular}{c} Grafting polymer monomers onto \\ the PDMS surface to create a \\ hydrophilic surface. \\ \end{tabular} } & Higher stability and & Low modification \\  & & &
\begin{tabular}{c} efficiency and uneven \\ surface \\ parameters of \\ the polymerization \\ process. \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Surface modification strategies for PDMS [69; 80; 81; 82].
# Characterization of Dynamic Blockage Probability in Industrial Millimeter Wave 5G Deployments
## 1 Introduction
Secondly, the industrial deployments are not fully stochastic, while the ones conventionally utilized in human body blockage models are. Instead, industrial machines are deployed on the grids and associated with production lines [15]. Dealing with semi-regular deployments is usually more complicated as compared to purely random ones, governed by, e.g., the Poisson point process [10]. In this paper, we develop the blockage model for complex IIoT deployments with machines performing periodic actions. To this aim, we combine the tools of photogrammetry and stochastic geometry on random lattice grids. The former is utilized to build the so-called transparency map of mechanical equipment utilized at the factory floor while the latter is further applied to build and solve the deployment scenarios of interest suitable for different types of industries by using standard methods of stochastic geometry techniques. Our main contributions are:  
* a composite model for blockage probability in industrial deployments of mmWave 5G technology based on photogrammetry and stochastic geometry;
* numerical results characterizing blockage probability in light and heavy industry environments as a function of machine deployment density and link distance;observations that: (i) direct UE-UE communications are feasible in sparse deployments or at small communications distances; (ii) base station (BS) height is a critical parameter affecting LoS blockage in UE-BS communications mode; (iii) to maximize BS-UE blockage probability one needs to deploy UEs at the highest possible height that typically coincides with machine heights. The rest of the paper is organized as follows. The related work is provided in Section 2. We present our system model in Section 3. In Section 4 we develop the blockage model by an individual machine. Further, in Section 5, we derive the blockage probability in industrial deployments. Numerical results are provided and discussed in Section 6. Conclusions are drawn in the last section.
## 2 Materials and Methods
### Data Selection  
The data used in this paper were live audio and video files provided by technicians inside certain substations and distribution stations. During their indoor inspections or routine checks, they found abnormal audible sound waves emitted from the operating switchgear or the surrounding environment, and they subsequently used the audio or video recording function of their smartphones to obtain audio and video files. In addition, the technicians, after further dismantling and defect detection, provided actual results and some on-site photographs, as shown in Figure 1 below.  
Figure 1: Actual defects in smartphone recording. (**a**) PD in a three-phase busbar contact box of switchgear; (**b**) Abnormal mechanical vibration in the side plate of a switchgear.  
The audio and video files provided were all over 10 s in length, using smartphones that are widely available, and the built-in microphone sampled at 48 kHz or 44.1 kHz. According to the detection results, the files can be classified into three types of audio: background noise, mechanical vibration, and PD. Twelve typical audio files were selected and numbered one by one in capital letters, as shown in Table 1, with the different switchgear briefly indicated by numbers.  
The four background noises come from different indoor environments, and the sound sources were human speech, metallic clang, birds chirping, and passing vehicle sounds. The mechanical vibration and PD came from the defects of the GIS, as well as other switchgears. The four mechanical vibrations contained normal vibration and abnormal vibration, and the abnormal vibrations came from actual mechanical defects, while the sound sources were current transformers (CTs), sheet metal parts, and side plates. Among the four PDs, two were from actual PD defects--the pressure relief flap and bus contact box discharges--and two were from simulated PD defects--single metal tip and two metal tip discharges.
# UAV Formation Trajectory Planning Algorithms: A Review
## 6 Problems of UAV Formation Trajectory Planning Algorithm
### Complex Environment Modeling Problem  
Most of the current formation trajectory planning algorithms are hypothetical ideal obstacles, but the actual operating environment of UAVs is complex and diverse, especially the detection and description of scenes such as complex concave obstacle environments and dense dynamic obstacles, which need further exploration.
## 4 Conclusions  
From the modeling and simulation of the hybrid chiller and the solar concentrator, the following conclusions have been obtained:  
Hybrid chiller for air conditioning. The hybrid chiller can produce cooling with both cooling systems coupled, or only with one, from \(x_{a}=0\) to \(x_{a}=1\). The compression system coupled with the Stirling engine can provide cooling power in the evaporator up to 53% higher than the heat supplied to the hot source of the heat engine. The mechanical power ratio between the compression and absorption system varies between 560 and 5 in the range of \(x_{a}\) from 0.05 to 0.95. When \(x_{a}\) is in the range of 0.2 to 0.45, the power ratio is between 130 and 30. This range may be suitable for the operation of the hybrid system. Regarding the heat ratio \(r_{q}=Q_{u}/Q_{e}\), it can be concluded that for obtaining greater cooling power than heat supply, the operation of the absorption system should be between \(x_{a}=0.2\) and 0.6, with Stirling engine efficiencies between 0.2 and 0.3 and condensing temperatures from 28 to 37 \({}^{\circ}\)C.  
Solar collector for hybrid chiller. The diameter of the absorber of the solar concentrator can be smaller than 30 cm, when the concentration ratio is greater than 20. This can contribute to distribute the radiation in the hot source over a larger area and to reach medium temperatures, rather than high temperatures, which contributes to improve the efficiency of the solar concentrator. The cooling power produced by the compression system can be up to 3 times higher than the heat supplied to the hot source of the Stirling engine, with \(T_{h}=200\)\({}^{\circ}\)C and \(\eta_{s}=0.3\). The efficiency of the solar concentrator is higher when the temperature in the hot spot is lower. With high \(T_{c}\), the COP of the absorption system increases with \(T_{h}\), whereas, with small \(T_{c}\), the change in COP with respect to \(T_{h}\) is negligible. The energy and economic savings of the proposed system, respect to a conventional electricity-driven air conditioning system, can be up to 60 MWh and $5300 at the end of the useful life of 25 years. Figure 13: Economic savings caused by the proposed system. **Author Contributions**: Conceptualization, G.R., C.J., J.d.J.R., A.Z. and M.V. ; investigation, G.R., C.J., J.d.J.R., A.Z., I.C., J.A.J., J.P. and M.V. ; resources, A.Z., I.C., J.A.J. and J.P.; writing--original draft preparation, G.R., C.J., J.d.J.R. and A.Z. ; writing--review and editing, G.R., C.J., J.d.J.R., A.Z., I.C., J.A.J., J.P. and M.V. ; funding acquisition, A.Z., I.C., J.A.J. and J.P. All authors have read and agreed to the published version of the manuscript. **Funding**: This research was funded by National Polytechnic Institute of Mexico (IPN) Project (SIP20200538, 2082), [PERSON] and [PERSON] thanks CONACYT for the scholarship granted. **Conflicts of Interest**: The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses or interpretation of data; in the writing of the manuscript or in the decision to publish the results. **Nomenclature**