esa-sceva/satcom-chunk-collection huggingface dataset:
# A Magnetic-Balanced Inductive Link for the Simultaneous Uplink Data and Power Telemetry
## 4 Optimizations of the Coil Position Parameters
### Selection of \(d_{12}\) for Avoiding a Significant Decrease of \(k_{23}\)  
The skew distance \(d_{12}\) denotes a small offset of the implant coil towards the external data coil along the positive direction of the Y axis as shown in Figure 3. Figure 6a shows the coupling coefficient (\(k_{23}\)) as a function of the coil separation (\(d\)) versus different skew distance (\(d_{12}\)). In the conventional two-coil inductive power link, the implant coil is coaxial with the external power coil (which means \(d_{12}=0\)) to maximize the coupling coefficient (\(k_{12}\)). However, if \(d_{12}=0\), \(k_{23}\) could decrease significantly and even approach zero when the coil separation (\(d\)) is small as seen for the red line (\(d_{12}=0\) mm) in Figure 6a, because there is also a magnetically-balanced point between the implant coil and the external data coil. We need to avoid this significant decrease of \(k_{23}\) in our operating range to keep the uplink data transmission reliable. We thus shift the implant coil towards the external data coil for a short distance (\(d_{12}=8\) mm in our case). The selection of \(d_{12}=10\) mm can benefit deriving larger \(k_{23}\). However, the improvement of \(k_{23}\) is remarkable only when the coil separation is small. Along with the increase of the coil separation, the values of \(k_{23}\) for different \(d_{12}\) tends to be almost the same. When the coil separation is 40 mm, the selection of \(d_{12}=10\) mm increases only 9.4% of \(k_{23}\) compared with the \(k_{23}\) when \(d_{12}=8\) mm. Furthermore, the offset of the implant coil could also affect \(k_{12}\), while \(k_{12}\) is a key parameter to the PTE. Figure 6b shows \(k_{12}\) versus different \(d_{12}\). As it shows, the increase of \(d_{12}\) causes the decrease of \(k_{12}\). Therefore, we select \(d_{12}=8\) mm instead of \(d_{12}=10\) mm to cause less impact on the WPT.  
Figure 5: Calculated coupling coefficient (\(k_{13}\)) versus different \(d_{13}\). There is an optimal \(d_{13}\) where \(k_{13}\) is minimized to approach zero, due to the balanced inside and outside magnetic flux from the external power coil.
## 3 In-Vehicle Engine Order Sound Fitting and Verification
### Engine Order Sound Synthesis Theory
#### 3.2.2 Fourier Transform and Analysis of Sound Signal of Engine Order  
Fast Fourier transform (FFT) is only suitable for stationary signal analysis. For the time-varying sound signal of the in-vehicle engine, an extended method of discrete Fourier transform, the short-time Fourier transform (STFT) method, needs to be used for analysis.  
The mathematical expressions of discrete short-time Fourier transform and discrete short-time Fourier synthesis of discrete time signals \(x(k)\) are [38]:  
\[STFT_{x}(n,m)=\sum_{k=-\infty}^{+\infty}x(k)w^{*}(k\Delta t-n\Delta t)e^{-j2 \pi(m\Delta f)k} \tag{8}\]  
\[x(k)=\sum_{n=-\infty}^{+\infty}\sum_{m=-\infty}^{+\infty}STFT_{x}(n,m)w(k \Delta t-n\Delta t)e^{j2\pi(m\Delta f)k} \tag{9}\]  
where: \(n\) is the serial number of the discrete time frame; \(m\) is the serial number of discrete frequency frame; \(\Delta t\) is the sampling period of time variable; \(\Delta f\) is the sampling period of the frequency variable.  
According to the principle of the Heisenberg uncertainty criterion of the short-time discrete Fourier analysis window function, the time resolution \(\Delta t\) and the frequency resolution \(\Delta f\) have a relationship: \(\Delta t\times\Delta f\geq 1/4\pi\), it is impossible to obtain high-precision time resolution and frequency resolution.
# The Potential of LEO Satellite-Based Opportunistic Navigation for High Dynamic Applications
## 4 Performance Characterization
### Effect of Error Sources
#### 4.2.4 Satellite Clock Drift  
The baseline scenario that contains thermal noise is now added constant satellites clock drifts. We set their values randomly for each satellite using a Gaussian distribution with a standard deviation set to 1 ppb for the intermediate case, and to 10 ppb for the worst case. These values can be considered as typical intermediate and worst-case values of the drift for an OCXO clock. Note that a satellite clock drift of 1 ppb (\(1-\sigma\)) will add an error to the Iridium Doppler measurement of \(\sim\)1.626 Hz (\(1-\sigma\)). We recall that the navigation filter defined in Section 2 does not correct for this error, as it is not available in the general context of navigation based on signals of opportunity.  
The results given in Figure 15 show that the position error is degraded by 81 m and 1.76 km, respectively, for 1 ppb (\(1-\sigma\)) and 10 ppb (\(1-\sigma\)) of the satellite clock drift. The intermediate and worst satellite clock drift cases degrade the user clock bias estimation by, respectively a few tens of milliseconds and a few hundred milliseconds. A satellite clock drift of 1 ppb (\(1-\sigma\)) does almost not affect the attitude error, while 10 ppb (\(1-\sigma\)) degrades the attitude estimation by 0.44\({}^{\circ}\). This shows that in terms of the attitude estimation, a satellite clock drift of 1 ppb (order of magnitude) can be tolerated without the need for clock drift corrections.  
The results obtained in this section show that the user position is highly sensitive to large satellite position errors, and to a lesser extent to the satellite velocity errors and the satellite clock drift errors. The attitude error, however, is slightly sensitive to large satellite position errors, and it is almost insensitive to the satellite velocity error and satellite clock drift.  
Figure 15: Influence of the satellite clock drift on (**a**) the position RMSE; (**b**) the attitude RMSE; (**c**) the receiver clock bias RMSE; (**d**) the receiver clock drift RMSE.
###### Abstract
On the other hand, the VAD method is not always practical, especially when the background noise is heavy or the sound field is complex. In this study, the conventional GSC method was modified to reduce the enhanced speech distortion without the VAD method. The step size of the adaptive algorithm in the GSC method was controlled by the cross-correlation coefficient between the cancelling signal and the error signal to reduce the distortion that occurred by the change of the speech energy. Furthermore, based on the excess mean-square error (MSE) of the LMS algorithm [30; 31] and the theoretical limits of the noise reduction performance [32], the sidelobe neutralization (SN) method was presented to reduce the noise component in the beamforming output signal of the GSC method to improve the denoising performance. This paper is organized as follows. Section 1 introduces the research background and reviews the relative academic achievements. Section 2 proposes the GSC method with the sidelobe neutralization method and the GSC method with the cross-correlation coefficient method. The modified GSC algorithm is given by combining them. Section 3 presents the implementation of the experiment and the result analysis. Section 4 provides the conclusions of this study.
## 3 Deliberate Attacks on IECPS
### Cyberattacks
#### 3.1.1 Replay Attacks  
RA is an attack against the data integrity of the system. The attacker records that the destination host has already received the information through illegal ways and sends the information repeatedly to achieve the purpose of deceiving the system [17]. In IECPS, attackers can illegally access system operation data, such as voltage, power, air pressure, and flow rate, through eavesdropping, interception, or packet capturing [18]. By repeatedly sending these data to the scheduling and control center, they prevent accurate assessment of the system's operational status. This hinders the formulation of effective scheduling strategies, ultimately compromising system stability. The attackers can also intercept the system's control commands, such as automatic generation control (AGC) frequency control signals [19], circuit breaker opening and closing commands [20], when the system is in normal operation, and constantly repeat the sending of control commands to cause erroneous actions of the system equipment, which affects the security of IECPS. Currently, some scholars are studying the detection techniques for RA, for example, by adding timestamps within the transmitted data or using more secure routing protocols [18; 21].  
Figure 3 illustrates the specific flow of the RA. Between time intervals \(t_{r}\) and \(t_{r+d}\), the attacker intercepts system information without disrupting system operations. At time \(t_{s}\), the attacker begins retransmitting the intercepted data to the target host, continuing until the conclusion of the attack. Thus, the RA can be represented as follows:  
\[y(t)=y[t_{r}+(t-t_{s})\text{mod}d],t\in\Big{[}t_{s_{r}},t_{s+(n+1)d}\Big{]}, \tag{1}\]  
where \(n\) indicates the number of replays.
## 5 Conclusions
Among them, the pitch axial translation of the MR had the highest impact on the BPE, while the yaw axial translation of the SSR had the lowest impact. The impact of the former was about four times greater than that of the latter. Therefore, to ensure the ABP accuracy required by the GEO microwave radiometer, stringent measures must be adopted to minimize the thermal distortions of the MR.
4. For any TDE examined in this study, once the scan azimuth of the ECF was specified, there was an approximately positive linear relationship between this TDE and the resulting BPE. On the other hand, once the TDE level was specified, most TDEs led to sinusoidal BPEs over a scan period of the ECF. The greater the TDE was, the more significant the sinusoidal trend in the resulting BPEs. When 13 TDEs existed simultaneously, the maximum fluctuation range of the BPEs was \(\sim\)62 \(\upmu\)rad during scanning of the Earth (i.e., the scan azimuth of the ECF ranged from 305\({}^{\circ}\) to 55\({}^{\circ}\)). This means that it is still feasible to use satellite attitude maneuvering to compensate for the thermally induced BPEs within the current NWP operational requirements. It should be noted that although the current actual ABP determination model (which is a rigorous model) can exactly compute the actual antenna beam pointing given the true thermal distortion parameters, it cannot be taken directly for the inverse calculation of the antenna thermal distortion parameters due to the problem of over-parameterization. Based on the above-mentioned conclusions, the actual ABP determination model can be further simplified in future research so as to be used to estimate the equivalent thermal distortion parameters at times of interest. Finally, it should be pointed out that the conclusions presented herein have a certain degree of universality for the three-reflector antenna that utilizes the offset Cassegrain antenna as the main body; and the method for deducing ABP determination models and analyzing the thermal distortion effects on BPE is a general method, which can also benefit the ABP determination and BPE analysis of other antenna configurations to a certain extent. Conceptualization, H.H. and X.T. ; methodology, H.H. and X.T. ; software, H.H. and X.T. ; validation, H.H., X.T., and H.L. ; formal analysis, H.H. and X.T. ; investigation, H.H. and X.T. ; resources, X.T. and H.L. ; data curation, X.T. and H.L. ; writing--original draft preparation, H.H. ; writing--review and editing, H.H. and X.T. ; visualization, H.H. ; funding acquisition, X.T. All authors have read and agreed to the published version of the manuscript. This research was funded by the National Key R&D Program of China under Grant 2018 YFB0505304, National Natural Science Foundation of China under Grant 41671409, and National Science Foundation of Henan Province under Grant 212300410096. Not applicable. The authors would like to thank all reviewers and editors for their comments on this paper. The authors declare no conflict of interest.
## 2 Materials and Methods
### Raman Micro-Spectroscopy  
The snow samples stored in glass bottles were melted at room temperature and filtered using 25 mm SPI-pore polycarbonate membrane filters with a pore size of 20 um (SPI Supplies, West Chester, PA, USA). While operating in a clean room, the filtrate was collected into a pre-cleaned beaker to avoid contamination. Five drops of the sample were deposited on an aluminum-covered slide and subjected to Raman analysis. Raman spectra were acquired with a Horiba LabRAM HR Evolution Raman micro-spectrometer (Horiba, Kyoto, Japan) equipped with a liquid-nitrogen-cooled CCD. A 633 nm He-Ne laser coupled with a ULF Bragg filter was used for excitation, and the laser power was adjusted to below 1 mW to avoid the thermal decomposition of the samples. Daily calibration was performed with a silicon slice using the 520.6 cm\({}^{-1}\) band.  
Field blank analyses were conducted to identify and exclude potential contamination during the entire sampling, storage, and preparation process. One hundred and fifty milliliters of Milli-Q water was analyzed in accordance with the same procedure described above.  
The investigated region was approximately 500 um \(\times\) 500 um. The region of interest was first optically imaged with 10\(\times\) magnification in order to identify and locate micro- and sub-microparticles, and then the Raman spectrum of each particle was collected with a 100\(\times\) magnification objective. Due to the presence of different particles, ranging from microplastic materials to carbon soot and inorganic particles, the acquisition parameters were modified to ensure the best signal-to-noise ratio, always starting from the minimal laser power (below 0.1 mW) to protect materials from thermal degradation. The exposure time was fixed from 10 to 30 s, with 3 to 6 spectral accumulations. The LabSpec Spectroscopy Suite (version 6.4.1.51) software was used for data analysis. Compound identification was carried out by comparing the acquired spectra with those stored in the PublicSpectra open Raman spectral database [[[https://publicspectra.com/](https://publicspectra.com/)]([https://publicspectra.com/](https://publicspectra.com/)), last access 9 January 2024] and rruff database ([[https://rruff-2.geo.arizona.edu/](https://rruff-2.geo.arizona.edu/)]([https://rruff-2.geo.arizona.edu/](https://rruff-2.geo.arizona.edu/)), last access 9 January 2024).
### Aim of the Paper  
Motivation for the research presented in this paper is the low effectiveness of the existing fishways, primarily in Europe [46]. In order to improve the design of new fishways and optimize the existing ones, hydraulic environment needs to be described by relevant variables and its dependency on the fishway geometry needs to be quantified. Fishways are often found to be ineffective for species with different morphological and ecological characteristics [31], and data acquired from hydraulic environment can be used in studies focusing on flow-fish interactions to evaluate fish behavior in response to hydraulic conditions and define turbulence at a scale relative to fish size [47]. River fragmentation analyses are mostly focused on the larger structures, such as hydropower dams [48], often overlooking smaller structures that make up the majority of barriers in the European rivers--68% out of more than 1.2 million barriers are structures less than 2 m high [49].  
Research focused on the fishway hydraulics, specifically in terms of turbulence, is needed to provide a base for numerical simulations and functional design to build upon. In this paper is presented the results of the experimental study conducted on two types of pool-type fishways that are considered to be nominally hydraulically efficient: pool-orifice and vertical slot. The aim of this paper is to investigate the hydraulic environment of the three-dimensional flow and turbulence measured in the physical fishway model with the goal of providing information on the Reynold's shear stress distribution that would facilitate their design in accordance with biocriteria boundaries defined in the literature.  
The paper is organized as follows. Section 1 (Introduction) provides insights into the research problem, presents the current state of the art from the literature review and formulates the aim of the research; Section 1 (Methodology) is devoted to the methodology framework--description of the experimental setup, data acquiring, data processing and data analyses; Section 3 (Results) presents the results of the Reynold's shear stresses for each fishway configuration; Section 4 (Discussion) synthesizes the common Reynold's shear stresses features of the fishway configurations that can be correlated with fishway geometry; and Section 5 (Conclusions) summarizes the main outcomes of the research.
## 2 Materials and Methods
### Signal Preprocessing  
The raw signal from the chosen dataset underwent several preprocessing steps.  
_Notch filtering._ The signal was first filtered with band-stop filters at 50 Hz and 100 Hz, to eliminate the noise from local electrical power sources and its first harmonic, which is the only known source for eventual perturbation of the recordings. Having as aim to explore the full range of frequencies contained in the recorded signal, no other additional filtering was applied.  
_Windowing._ Following normal signal processing practice, instead of exploring the entire signal waveform at once, the filtered electrical signal was initially partitioned into fragments of relatively short durations. More precisely, in a step of 5 min, seven different windows of fixed length, namely the last 15 s, 30 s, 1 min, 2 min, 5 min, 10 min and 30 min, were extracted from the signal (refer to Figure 4). As this is a relatively new domain of research, there is a lack of knowledge of the temporal extent at which the signal information  
Figure 3: Recorded signal from three plants included in the analyzed dataset (after a band-filtering at 50 Hz and 100 Hz). “Day -2” and “Day -1” represent the two days before the contamination of the plants, whereas “Day 10” and “Day 11” are the tenth and eleventh days after the contamination. The light yellow indicates the periods of the day where there was prominent daylight, whereas the grey indicates the dark periods.  
characterizing the stressed plant state could be discriminated. Therefore, to explore the temporal extent in this context, rather than taking only one signal window at each sampling step, we choose to work with seven different window sizes. All of these seven windows will represent a single sample for a given plant. Hence, using this approach for the taken 96 h of recordings, we ended up with a set of 1152 samples for each plant (288 samples per single day).  
LabellingEach of the samples was labelled either as normal ('0') or as infested /stressed ('1') conforming to the meta-data information, i.e., considering the information if the sample in question was recorded before or after the contamination.
###### Abstract  
There is a need for developing new sorbents that incorporate renewable resources for the treatment of metal-containing solutions. Algal-polyethyleneimine beads (APEI) (reinforced with alginate) are functionalized by grafting amidoxime groups (AO-APEI). Physicochemical characteristics of the new material are characterized using FTIR, XPS, TGA, SEM, SEM-EDX, and BET. AO-APEI beads are tested for the recovery of Sr(II) from synthetic solutions after pH optimization (\(\approx\) pH 6). Uptake kinetics is fast (equilibrium \(\approx\) 60-90 min). Sorption isotherm (fitted by the Langmuir equation) shows remarkable sorption capacity (\(\approx\) 189 mg Sr g\({}^{-1}\)). Sr(II) is desorbed using 0.2 M HCl/0.5 M CaCl\({}_{2}\) solution; sorbent recycling over five cycles shows high stability in terms of sorption/desorption performances. The presence of competitor cations is studied in relation to the pH; the selectivity for Sr(II) is correlated to the softness parameter. Finally, the recovery of Sr(II) is carried out in complex solutions (seawater samples): AO-APEI is remarkably selective over highly concentrated metal cations such as Na(I), K(I), Mg(II), and Ca(II), with weaker selectivity over B(I) and As(V). AO-APEI appears to be a promising material for selective recovery of strontium from complex solutions (including seawater).  
Keywords: algal-alginate-polyethyleneimine beads; amidoximation; uptake kinetics; sorption isotherm; desorption; selectivity seawater; strontium +
Footnote †: journal:  
_Article_
## 5 Conclusions
In this research, a single objective function that combines these two objective functions was utilized. SDCS can be implemented using MinSum and MinMax objective functions within the scope of multi objective optimization. The comparative analysis with the tested MH algorithms shows that the SDCS method is more precise and efficient, providing cost savings for UAV system designers through reduced energy consumption and processing time. These findings highlight the significance of the SDCS method in enhancing the sustainability of UAV missions. Moreover, the results of this study are promising for applying the proposed SDCS approach in many engineering applications, particularly concerning cost savings. A systematic framework has been introduced, supported by tools for the effective control of the quadcopters. By utilizing the SDCS method using ReaX, the dynamic behavior of the quadcopter is abstracted and desired control objectives are provided. The SDCS method automatically computes a controller and converts it into Simulink, using an appropriate language to ensure compliance with system specifications. This approach constructs symbolic models for the dynamic behavior and path planning objectives for unmanned systems and increases practical applicability. The future roadmap includes developing guidelines for applying the SDCS approach to real-world UAV missions, accommodating various combinations of robotic systems. Additionally, a strategy will be devised to implement a task-scheduling algorithm specifically tailored for queuing quadcopters in aerial surveillance contexts. Furthermore, future studies will focus on developing a dedicated UAV synchronous programming environment that features symbolic control algorithms. The implementation of optimal control algorithms to various objectives is also envisioned. Lastly, integrating SDCS with stochastic models presents a promising approach for enhancing multi robot and human-robot collaboration. This research received no external funding. Not applicable. Data Availability StatementData are contained within the article. The author declares no conflicts of interest.