esa-sceva/satcom-chunk-collection huggingface dataset:
# Recent Progress on Vegetation Remote Sensing Using Spaceborne GNSS-Reflectometry
## 3 Existing Problems
### Improve Our Understanding of the Mechanism Model for Vegetation  
The goal of a GNSS-R/GNSS-IR model for vegetation is to establish the relationship between surface vegetation parameters and the GNSS reflection signal. That is to establish the relationship between vegetation parameters, observation geometric parameters, anddelay Doppler diagram or multi-path observables (SNR, phase, and pseudo-range). Although the N-L multi-path forward GPS model can simulate the influence of vegetation parameters on multi-path signals, the premise is that the receiver can only receive the specular reflection energy of vegetation in the First Fresnel Zone (FFZ). However, several works published recently have pointed out that the noncoherent energy coming from the outside of FFZ should not be ignored during the calculations [61; 62].  
When calculating the scattering characteristics of vegetation, the dielectric constant of the vegetation is input into the circular polarization reflection coefficient, and information such as the antenna model, observation geometry, and system parameters are coupled, and finally, SNR, phase, and pseudo-range information are obtained. The calculation of the vegetation scattering characteristics in the model is without considering incoherent scattering, and at the same time, it is unable to simulate the scattering, reflection, and attenuation information of the navigation satellite signal in the vegetation layer. Most of the existing microwave scattering models are for monostatic radar backscattering models or emissivity models for radiometers, and there are relatively few bistatic scattering models for GNSS-R. In addition, the polarization considerations in the existing models are lacking. The subsequent models need to consider the characteristics of circular polarization and the scattering capabilities of different polarizations combined with circular polarization and linear polarization. Only the model that has this function can effectively analyze and mine the polarization characteristics, carry out the inversion of the relevant vegetation biomass according to its polarization characteristics information, and use the polarization information to improve the accuracy of the inversion [51; 52; 53].  
Accurately understanding and describing the microwave scattering mechanism of rough surfaces and vegetation parameters is the most important theoretical basis for GNSS-R surface parameter remote sensing. It can be used for the analysis and interpretation of satellite observations, satellite data simulation, and satellite data assimilation. Theoretical models can also be employed for the development of quantitative surface parameters' retrieval algorithms, and they are the key mechanism tools for new sensor design [67]. Therefore, we must vigorously promote and strengthen the research on GNSS-R remote sensing theoretical modeling in the follow-up study.
# Wavelength Selection for Detection of Slight Bruises on Pears Based on Hyperspectral Imaging
## 3 Results and Discussion
### PLS-DA Modeling Based on Two Characteristic Wavelengths  
Finally, the two characteristic wavelengths were extracted by the PCA-ROC analysis: 472 and 967 nm. The spectral data of 90 samples (45 bruised samples and 45 normal samples) at the characteristic wavelengths were used to establish the PLS-DA model as the modeling set, and 30 samples (15 bruised samples and 15 normal samples) were used to predict the accuracy of the model as the prediction set. The results were compared with those of the full-wave-band PLS-DA modeling result and are shown in Table 2.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Wavelength/nm** & **AUC** \\ \hline
472 & 0.992 \\
544 & 0.864 \\
655 & 0.728 \\
688 & 0.663 \\
967 & 0.980 \\ \hline \hline \end{tabular}
\end{table}
Table 1: The area under the curve (AUC) of different wavelengths by the receiver operating characteristic (ROC) curve analysis.  
Figure 6: The receiver operating characteristic (ROC) curves at different wavelengths of modeling samples: (a) 472 nm; (b) 544 nm; (c) 655 nm; (d) 688 nm; (e) 967 nm.  
It can be concluded from Table 2 that the recognition results by the model based on characteristic spectral bands were ideal. All of the 45 normal samples of the modeling set and the 15 normal samples of the prediction set were correctly identified, while 44 of the 45 bruised samples of the modeling set and all 15 bruised samples of the prediction set were correctly identified. The overall accuracy of the modeling and prediction sets of the model established on the two characteristic wavelengths (472 and 967 nm) reached 98.9% and 100%. The accuracy was similar to that of the model established on the full band, which was 100% of the modeling set and 100% of the prediction set. However, by extracting the characteristic wavelength, the number of wavelengths needed in the detection process was greatly reduced, which was more suitable for on-line detection. Compared with previous studies which detected bruised pears using the hyperspectral imaging technique [4; 9; 10], this paper reduced the amount of wavelengths to two using PCA-ROC analysis and improved the detection accuracy of the model.
# An Introduction of a Modular Framework for Securing 5G Networks and Beyond
## 5 Conclusions  
A D2D communications network with 5G capability is made up of several systems backed by different technologies. This prompted the creation of several security solutions that deal with security for particular applications or layers. In addition, new use cases for accessing other services from SPs in various domains are made possible by 5G network services, posing additional security difficulties. Consequently, a comprehensive security solution that handles these problems is required. End-users will frequently access services from several SPs using their UE, which will present a new security risk. Additionally, infrastructure and security management may be shared amongst SPs. This article examined security in D2D communications, 5G, and beyond. It described the system's levels, including those that have been addressed in related works and those which still require attention. A security framework was proposed that outlined the security levels and entities involved in the authentication and authorisation processes. For the proposed security framework, it established the underlying security protocols, which were fully verified for security guarantees and appraised for efficiency. As part of an integrated security solution, the designed underlying security protocols using the suggested framework were streamlined to certain system levels and solved various security challenges. The protocols, however, can be used as a standalone solution, sharing some security context to comply with 5G security standards while permitting interoperability with third-party solutions without compromising security at any level.  
Current studies have focused on developing security solutions that apply to one layer without considering the security of the layer below or above. The future direction of the research in this article is to extend the framework's application to the next-generation mobile network and other systems such as Internet of Things (IoT) and autonomous vehicles. This framework could develop security mechanisms and evaluate their effectiveness and interoperability as an integrated solution.  
Conceptualisation, E.K.K.E., M.A. and J.L.; methodology, E.K.K.E. and M.A.; validation, E.K.K.E. and M.A.; investigation, E.K.K.E.; writing--original draft preparation, E.K.K.E.; writing--review and editing, E.K.K.E. and M.A.; supervision, M.A. and J.L. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The authors declare no conflict of interest.  
Figure 7: Integrated Security Solution.
# Implementation of Fault-Tolerant Control for
## 5 Simulation Results
### Simulation 4  
To test the robustness of the fault-tolerant characteristics of the proposed algorithm, simulations with multiple faults were performed with the three control algorithms Equations (25), (46) and (48), for which the parameters were selected in Section 5.2. Multiple faults/failure functions were assumed to be  
\[\left\{\begin{array}{l}\tau_{1}^{t}=\tau_{1}+f_{1}(t)\;t>5\\ \tau_{2}^{t}=(1-\rho_{2}(t))\tau_{2}+f_{2}(t)\;t>5\\ \tau_{3}^{t}=(1-\rho_{3}(t))\tau_{3}\;t>5\end{array}\right. \tag{52}\]  
where \(f_{1}(t)=60\), \(\rho_{2}(t)=0.4\sin(\pi t)\), \(f_{2}(t)=60\sin(\pi t/2)\), and \(\rho_{3}(t)=0.7\sin(\pi t)\).  
In Figure 7, the estimation results with multiple joint faults have been shown. Multiple faults simultaneously occurring at each joint seemed to burden the control system more than a single fault did. However, the proposed algorithm still resulted in smaller position-tracking errors than the conventional algorithm, demonstrating fault-tolerant characteristics, as seen in Figure 8.  
Figure 5: Estimated fault with the different values of \(\rho_{2}(t)\). (**a**) Joint 1; (**b**) Joint 2; (**c**) Joint 3.  
Figure 6: Tracking error at each joint with different values of \(\rho_{2}(t)\). (**a**) Joint 1; (**b**) Joint 2; (**c**) Joint 3.  
**Remark 1**.: _As mentioned in Section 1, the accuracy of fault estimation highly affects the performance of AFTCs, so Simulation 1 discussed the design of ESO. As a trade-off between the convergence and the peaking value of estimation results, the parameters of the observer were selected by using a trial-error technique, as shown in the Simulation 1 results. In Simulations 2, 3, and 4, the outperformance of the proposed controller was presented by the tracking trajectory error results. In Simulation 3, the robustness of the proposed controller was described with a high magnitude of fault. In this case, PFTC-SMC and AFTC-SMC could not guarantee stability of the system. However, the proposed AFTC-SSMC could keep the system stable and showed acceptable performance results with the tracking trajectory error inside \(10^{-3}\) rad. In Simulations 2 and 4, single and multiple faults were presented. Compared with the two fault-tolerant controllers without the consideration of the synchronization error, the proposed controller can reduce the picking phenomenon due to the simultaneous approach to zero at each joint of the synchronization technique. This characteristic of synchronization control can act to prevent the slow response of AFTCs._
## 1 Introduction
[30] designed a NIR ratiometric probe, CyDPA2 that targets Tau aggregates. They evaluated it in vitro and ex vivo and reported an enhancements of absorption ratio and fluorescence intensity in a p-Tau concentration-dependent manner. In addition, fluorescence microscopy and gel staining studies demonstrated CyDPA2-labeled Tau aggregates. In a previous report [31], we proposed an optical method that enables measurements of the CSF biomarker concentrations utilizing fluorescence probes, without the need to perform a lumbar puncture. This method is less invasive and has minimal risk, pain, and side effects. The method includes several stages. First, fluorescent probes [23; 24; 25; 26; 27; 28; 29; 30; 32], which bind specifically to the two biomarkers in the CSF, are injected to the blood. Second, a miniature needle with an optical fiber is inserted into the epidural fat, which is located several millimeters from the CSF, without penetrating the dura matter. The fluorescent biomarkers are then excited by a laser, which reaches the CSF through the optical fiber located inside the needle. Finally, the fluorescence intensities of both biomarkers are measured and used for the estimation of the biomarkers concentration ratio. Since this optical method does not require CSF collection, the dura matter is not penetrated and a smaller needle may be used. Therefore, the lumbar puncture risks, which include CSF leakage, traumatic taps, spinal cord injuries, and severe headaches, are significantly reduced. In addition, as opposed to other similar optical methods [12; 13] the concentration ratio estimation using this method does not require a priori information about the tissue optical and anatomical properties. In our previous report [31] we introduced a theoretical model that enables to create the relation between the measured fluorescence emission and the biomarkers concentration ratio. The method was validated using Monte Carlo simulations and its accuracy was tested in vitro using multi-layered tissue phantom. Here we further assess the method's accuracy using mice. Miniature tubes containing two fluorescent probes with several concentration ratios were implanted in the mice. The tubes were inserted into two different locations: subcutaneously, and deeper in the abdomen. The fluorescent probes were excited separately and their fluorescence intensity was measured. Using a simple calibration curve, the concentration ratio of the fluorescent probes in each tube was extracted. The extracted ratios were compared to the true ratios and an error analysis was performed.
## 5 Application Areas
In robotics, magnetic gears enable precise motion control and wear-free power transmission due to their contactless operation. Magnetically driven variable transmission mechanisms developed in this field offer natural overload protection and backdrivability, making them especially attractive for exoskeletons and legged robots despite their compact design [120,121]. Furthermore, an actuation module based on a coaxial magnetic gear, combined with a disturbance observer-based torque control scheme, eliminates the need for external sensors and integrates the flexibility of magnetic coupling with force feedback capability [122]. Aerospace applications are among the fields where system weight and reliability are critical. Therefore, the torque-to-mass ratio advantages offered by magnetic gears become particularly significant in low-torque systems. In various studies, two different small-scale concentric magnetic gear prototypes were developed, and it was demonstrated that the second prototype provided a specific torque of 44.7 Nm/kg, offering a performance comparable to fixed-wing aircraft transmissions [123]. In addition, volumetric torque density optimization was achieved through parametric designs based on different rotor magnet configurations [124]. A magnetic gear system rated at 15.9 kW with a gear ratio of 12.4:1, designed in accordance with NASA's system requirements for electric vertical take-off and landing (eVTOL) aircraft, demonstrated a specific torque of 53 Nm/kg. This system was verified to be a suitable solution for flight propulsion systems when integrated with high-speed motors [41]. All these examples demonstrate that magnetic gear systems contribute significantly, not only in terms of efficiency gains but also in system reliability, ease of maintenance, and structural integration capability, across a wide range of sectors.
# Experimental Investigation into the Thermal Performance of Personal Cooling Mechanisms
## 1 Introduction
### Individual Thermal Comfort and Sensation  
Individuals' thermal comfort and sensation are influenced by environmental factors such as air temperature, relative humidity, mean radiant temperature, air velocity, metabolic rate, and clothing [34]. Thermal comfort reflects a person's contentment with the thermal environment, typically assessed through surveys and mathematical models. The thermal point scale that evaluates user comfort is measured using the Comfort Sensation Vote (CSV) following ISO 10551-19 [35], as shown in Table 1.  
On the other hand, thermal sensation refers to the individual's perception of the thermal environment. It is quantified using the standard ASHRAE 55-23 [36], outlining the conditions necessary for a satisfactory indoor environment in buildings and other occupied spaces. This standard specifies the environmental conditions, including air temperature, relative humidity, air velocity, mean radiant temperature of surrounding walls and objects, activity level of occupants, and clothing type. The standard uses the PMV (Predicted Mean Vote) and PPD (Predicted Percentage Dissatisfied) calculations based on the ISO 7730-2005 standard [37] with the 7-point thermal sensation scale in Table 2, which is derived from the heat balance of the human body. The PMV is calculated using estimations of metabolic rate based on the type of work and thermal resistance of clothing.  
\begin{table}
\begin{tabular}{c c} \hline
**Level** & **Thermal Comfort** \\ \hline \(-3\) & Very uncomfortable \\ \(-2\) & Uncomfortable \\ \(-1\) & Slightly uncomfortable \\ \(0\) & Neutral \\ \(1\) & Slightly comfortable \\ \(2\) & Comfortable \\ \(3\) & Very comfortable \\ \hline \end{tabular}
\end{table}
Table 1: Seven-point thermal comfort scale per the standard ISO 10551-19.  
\begin{table}
\begin{tabular}{c c} \hline
**Level** & **Thermal Sensation** \\ \hline \(-3\) & Cold \\ \(-2\) & Cool \\ \(-1\) & Slightly cool \\ \(0\) & Neutral \\ \(1\) & Slightly warm \\ \(2\) & Warm \\ \(3\) & Hot \\ \hline \end{tabular}
\end{table}
Table 2: Seven-point thermal sensation scale per standard ASHRAE 55-23.
# Optical Design and Stray Light Analysis of Underwater Spectral Radiometer
###### Abstract  
Underwater spectral detection plays an important role in the study of the underwater environment, ecology, oceanography, and environmental monitoring. A kind of underwater spectral radiometer that can observe the distribution of underwater spectral radiation bidirectionally has been developed. The flat-field concave holographic grating is used as the only optical component, the optical design parameters are optimized, and the system is miniaturized. The mechanism of stray light generation in the spectrometer is studied, and a method of suppressing stray light is proposed and simulated. The level of stray light in the system is suppressed to the order of \(10^{-4}\), the signal-to-noise ratio of the system is improved, and the ability to detect weak light is enhanced. The wavelength calibration experiment was completed, and the experimental results show that the wavelength resolution of the underwater spectral radiometer is better than \(3\,\mathrm{nm}\). Finally, the quantitative relationship between spectral irradiance and digital output is obtained through radiation in the calibration of the system.  
spectroscopy and spectroscopic instruments; optical design; stray light analysis and suppression; flat-field concave holographic grating Article
## 1 Introduction
The main purpose of this paper is to introduce a multitemporal approach that could exploit the entire Sentinel-2 time series for the identification of burned areas, and to provide suggestions to address the future development of the procedure in order to refine it with additional methods. To test the effectiveness of the proposed procedure, the 2017 Italy wildfires were considered as a case study. Three spectral indices were used to identify burned areas, and results were compared to Copernicus EMS products.
## 2 Related Literature and Problem Statement
### Literature Review
As it is a fragile method, the watermark image cannot be extracted if manipulation occurs in the watermarked image. The method is also less resistant to attacks. [PERSON] et al. (2021) proposed another NST-redundant DWT (RDWT)-based method for ensuring better imperceptibility and strong robustness. The method guarantees improved imperceptibility (PSNR = 57.06 dB) and strong robustness (normalized correlation, NC = 0.99) against various attacks. At first, 1L NST is applied to the host image and selected contourlet sub-bands. Then, RDWT is applied to it. Then, wavelet sub-bands are selected and divided into \(8\times 8\) blocks. Finally, the watermark bit is inserted into each block of the host image. Thus, the watermarked image is produced after performing a reverse transformation. The method proves robustness against motion cropping, sharpening, HE, MF, LPGF, GN, SN, SPN, GF, MF, JPEG compression, and blurring attacks. But, they do not use any security technique in the watermark image. Additionally, the capacity to insert a watermark is not estimated. In 2021, [PERSON] and [PERSON] [22] proposed another DWT-SVD-based efficient image watermarking technique. The method has better imperceptibility (PSNR > 36 dB) and is robust against GN, SPN, SN, rotation (45\({}^{\circ}\)), cropping, stretching, and HE attacks. FPD problems can be solved by this method. But, it does not show quantitative results for FPD. Also, filter and hybrid attacks are not observed. They do not use any encryption technique to ensure watermark image security. Also, embedding capacity is not calculated. [PERSON] et al. [23] proposed another blind hybrid NSCT-DWT-SVD-human visual system (HVS) based image watermarking method for ensuring better imperceptibility and robustness. At first, 1L NST is applied to the host image to extract low-frequency sub-band, and then 2L DWT is applied to it to extract sub-blocks. SVD is applied to each sub-block, and the best position for embedding the watermark is selected using HVS. The Arnold map encrypts the watermark image that is embedded into the singular values of the host image. Thus, the watermarked image is generated. FPD problems can be avoided by this method. The method ensures better imperceptibility (PSNR = 46.56 dB) and is robust against GN, SN, GF, MF, JPEG compression, cropping, shear center (CC), and scaling attacks. But, the method is less robust against rotation attacks. Also, AF, SPN, resizing, hybrid attacks and embedding capacity are not observed.
## 3 Proposed Model
### Testing Process  
In the testing process, the signal did not pass through the GPR target path (dotted line in Figures 6 and 7). This model is shown in Figure 8. The user data \(u[k]\in\) {0,1} are magnetized into the 2D magnetic signal \(a[j,k]\in\) {\(-\)1,1} (where \(-\)1 and 1 represent opposite poles of the magnetic field) on the medium of the BPMR systems. When the header reads back the data from the medium, \(y[j,k]\) of the header output is distorted by interference from the surrounding data, additive white Gaussian noise (AWGN), media noise, and TMR. The readback signal \(y[j,k]\) was then split into three branches.  
First, \(y[j,k]\) was fed to equalizer \(\mathbf{F}_{\text{2 way}}\) and converted into signal \(z_{\text{2 way}}[j,k]\). Signal \(z_{\text{2 way}}[j,k]\) was detected by a 1D VA and used to estimate the interference in \(z_{\text{4 way}}[j,k]\).  
Second, \(y[j,k]\) was fed to equalizer \(\mathbf{F}_{\text{4 way}}\) and converted into signal \(z_{\text{4 way}}[j,k]\). With the estimated interference from signal \(z_{\text{2 way}}[j,k]\), we can remove the interference in the signal \(z_{\text{4 way}}[j,k]\) to achieve a signal including 1D interference. Therefore, this signal is detected by the 1D VA and used to estimate the interference in \(z[j,k]\).  
Third, \(y[j,k]\) was sent through the equalizer \(\mathbf{F}_{\text{8 way}}\) and was converted into the signal \(z[j,k]\). With the estimated interference from the signal \(z_{\text{4 way}}[j,k]\), we can also remove the interference in \(z[j,k]\) to achieve a signal distorted by the 1D interference. Then, this signal was detected by the 1D VA and signal \(\bar{a}[j,k]\) (estimation of \(a[j,k]\)) was obtained. Finally, the signal \(\bar{a}[j,k]\) underwent demodulation to restore the original data \(\bar{a}[k]\).