esa-sceva/satcom-chunk-collection huggingface dataset:
# Crawling Magnetic Robot to Perform a Biopsy in Tubular Environments by Controlling a Magnetic Field
## 3 Actuating Principle of the CMR  
### Magnetic Navigation System  
We developed a magnetic navigation system to control the various motions of the CMR. As shown in Figure 2a, the MNS is composed of three coils, i.e., a Helmholtz coil that generates a uniform magnetic field along the x-axis, a y-directional uniform saddle coil that generates a uniform magnetic field along the y-axis, and a z-directional uniform saddle coil that generates a uniform magnetic field along the z-axis. Moreover, the CMR is controlled inside of the workspace which is in a magnetic field controlled by a Helmholtz coil and two uniform saddle coils. Because the external magnetic fields generated by each coil of the MNS are orthogonal to one another, the MNS can create a three-dimensional external magnetic field. The external magnetic field generated from the MNS can be expressed as the following equation [23]:  
\[\textbf{B}_{e}=\left[\begin{array}{cc}0.7155\frac{h_{1}n_{h}}{r_{h}}&0.6004 \frac{layer_{1}ny}{r_{ny}}&0.6004\frac{ia_{1}n_{uz}}{r_{nz}}\end{array}\right]^ {T} \tag{1}\]  
where \(i\), \(n\), and \(r\) are the current, the number of coil turns, and the radius of the coil, respectively. The subscripts \(h\), \(uy\), and \(uz\) represent the Helmholtz coil, y-directional uniform saddle coil, and z-directional uniform saddle coil, respectively. The coefficients are only affected by the permeability of the medium in the workspace. Figure 2b shows the workflows of the system. Operators can monitor the orientation and motions of the CMR via camera and the information of the applied magnetic field, such as magnitude, direction, and frequency, through the control panel. When the operator manipulates the joystick to control the motions of the CMR, the signals generated by the joystick are converted into current information and then transmitted to the power supplies connected to the pairs of electromagnetic coils that generate the magnetic field. Figure 2c depicts a constructed MNS and experimental setup.  
The magnetic torque, **T**, exerted on a permanent magnet due to the magnetic field can be expressed as follows:  
\[\textbf{T}=\textbf{m}\times\textbf{B} \tag{2}\]  
where **m** and **B** are the magnetic moment of a permanent magnet and the magnetic flux density of the external magnetic field generated by the current flowing through the coil or by other permanent magnets.  
Figure 2: (**a**) MNS composed of a Helmholtz coil and two uniform saddle coils to generate an external precessional magnetic field. (**b**) Control workflows of the MNS. (**c**) Constructed MNS and experimental setup.
## 3 Experimental Results
### Experimental Evaluation Index  
The difference between the mean brightness, \(B\), and the mean gradient, \(T\), of the pixels in the shadow area and that between the mean brightness, \(B_{\text{NSD}}\), and the mean  
Figure 8: Comparison of shadow compensation results in aerial image #5. (**a**) Original satellite image #3. (**b**) Initial shadow detection result. (**c**) Final shadow detection result. (**d**) LCC result. (**e**) HM result. (**f**) GT result. (**g**) CSR result. (**h**) the WLC result. (**i**) The proposed method’s results. Red pixels in (**b**,**c**) are detected shadows.  
Figure 7: Comparison of shadow compensation results in satellite image #4. (**a**) Original satellite image #2. (**b**) Initial shadow detection result. (**c**) Final shadow detection result. (**d**) LCC result. (**e**) HM result. (**f**) GT result. (**g**) CSR result. (**h**) The WLC result. (**i**) The proposed method’s result. Red pixels in (**b**,**c**) are detected shadows.  
gradient, T\({}_{\text{NSD}}\), in the non-shadow area are the main indexes with which to measure the shadow compensation effect [26]. According to the brightness characteristics after shadow compensation, the normalized difference ratio is calculated in accordance with Equations (9) and (10). The compensation quality index, \(Q^{B+T}\), is calculated using Equation (11) after counting the brightness difference, \(\Delta B\), and average gradient, \(\Delta T\), in the non-shadow area. Additionally, the quality of pixel compensation in the shadow area is calculated. Then, the compensation result can be quantitatively evaluated.  
\[\Delta B^{2}=\left|\frac{B-B_{\text{NSD}}}{B+B_{\text{NSD}}}\right|^{2} \tag{9}\]  
\[\Delta T^{2}=\left|\frac{T-T_{\text{NSD}}}{T+T_{\text{NSD}}}\right|^{2} \tag{10}\]  
\[Q^{B+T}=\Delta B^{2}+\Delta T^{2} \tag{11}\]
## 4 Conclusions  
Two-equation turbulence models, Std. k-\(\varepsilon\), RNG k-\(\varepsilon\), Std. k-\(\omega\), and SST k-\(\omega\), have been compared with the Gamma-Theta (GT) transitional model, and it has been found that the Gamma-Theta model is the most consistent model with the experimental values of the ERCOFTAC T3A test case.  
The transition from laminar to turbulence is shortened with increasing turbulence intensity by changing it from 1% to 10%.  
In the case where the inlet-turbulence intensity is 1%, the flow occurs directly as laminar, and this time, there is no laminar and turbulent transition region.  
It has also been observed that with the increase in the inlet-turbulence intensity in the flow over the plane plate, the transition to turbulence becomes easier, the laminar region shortens, and the transition region to turbulence narrows as the turbulence intensity increases. These results are also supported experimentally since they were also found in the experimental study of [PERSON] et al. [25].  
In the case where the inlet-turbulence intensity is 10%, the flow occurs directly as turbulent, and this time, there is no laminar and turbulent transition region.  
The most suitable inlet-turbulence-intensity value with the experimental results of the ERCOFTAC T3A test case is found as Tu = 3.3%.  
Conceptualization, E.P.; Methodology, E.P.; Software, H.A.E.; Validation, H.A.E.; Formal analysis, M.S. and H.A.E.; Investigation, M.S.; Writing--original draft, H.A.E.;Writing--review & editing, M.S. and E.P.; Visualization, H.A.E.; Funding acquisition, M.S. All authors have read and agreed to the published version of the manuscript.  
This research was funded by YOK-Council of Higher Education in Turkey grant number 100-2000.  
Not applicable.  
The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.  
We would also like to thank [PERSON] and [PERSON] for their assistance.  
Author [PERSON] was employed by the company PFMuhendislik. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
# Optical Beamforming Networks for Millimeter-Wave Wireless Communications
## 4 OBFNs with Phase Shifter Architectures
### Matrix Architectures
PAAs using phase shifter architectures addressed above are not squint-free, since the phase shift provided by a phase shifter does not depend on the RF frequency, causing a change in the beam angle under different RF frequencies. However, there is a great number of applications with limited bandwidth, while exploiting phase shifters in a TTD architecture can reduce its complexity and cost [18; 20; 112; 113]. For instance, one architecture combined with the phase shifters and TTDs has been proposed in [92; 114]. In these two architectures, phase shifters and TTD can realize fine tuning and coarse tuning, separately. This feature is beneficial for scanning the beam in a broad coverage, and achieving a balance between bandwidth and system complexity. Therefore, OBFN architectures with a phase shifter array and TTDs are conducive to PAAs with a limited bandwidth.
# Mixed Order Fractional Observers for Minimal Realizations of Linear Time-Invariant Systems
## 5 Discussion
### Other Assumptions  
The proposed observers for system (7) can be generalized for multi-input multi-output (MIMO) systems. Consider the completely controllable and observable MIMO system  
\[\left\{\begin{array}{l}{}_{0}D^{\alpha}x=Ax+Bu\\ y=Cx+Du\end{array}\right. \tag{23}\]  
where \(x:[0,\infty)\rightarrow\mathbb{R}^{n}\), \(u:[0,\infty)\rightarrow\mathbb{R}^{m}\), \(y:[0,\infty)\rightarrow\mathbb{R}^{p}\) and the matrices \(A,B,C,D\) having suited dimensions. Since the system is observable, for any arbitrarily chosen matrix \(F\), there exists \(G\) such that \(F=A-GC\). Hence, defining \(B^{\prime}=B-GD\) the state equation can be rewritten as  
\[{}_{0}D^{\alpha}x =Fx+Gy+\left(B-GD\right)u=Fx+Gy+B^{\prime}u\] \[=Fx+\sum_{i=1}^{p}G_{i}y_{i}+\sum_{i=1}^{m}B_{i}^{\prime}u_{i}\]where \(G_{i},B_{i}^{\prime}\) are the columns of \(G,B^{\prime}\), respectively. Equations (8) and subsequent are accordingly modified by changing \(gy+bu\) to \(\sum_{i=1}^{m}G_{i}y_{i}+\sum_{i=1}^{p}B_{i}^{\prime}u_{i}\). When \(\alpha=\beta=1\), this generalizes the procedure in [33].  
Note that we have assumed known the DO of the plant (23). An independent estimation procedure of it, that can be coupled to the proposed observers, is presented in [14].
## 8 Conclusions  
In this paper, the impact of eccentric tolerances on relevant performance indices of MPMSMs was identified and described for different slot/pole combinations, as well as compared with equivalent machines with conventional monolithic stator. Both static and dynamic eccentricity were assessed for five slot/pole combinations, and the radial forces, cogging torque, back-EMF, and mean torque were analyzed. It was found that:  
* Radial forces on machines with SE and DE scale with the slot number and pole number, and that the severity of these forces is lower in the case of modular machines with a high value of slots per pole per phase. In addition, a high-frequency force ripple of significant magnitude is present in machines with a slot number and pole number close to each other.
* When assessing the cogging torque, additional harmonic components (AHC) of severe magnitude are generated due to eccentricity. In this regard, machines which slot number is close to its pole number are very sensitive to eccentricity and develop a substantial cogging torque increase of up to 400%. There are no significant differences between DE and SE in terms of the cogging torque increase magnitude. Nevertheless, the harmonic order of the AHC generated by DE corresponds to the slot number and multiples, while the order of the AHC generated by SE is equivalent to pole number and its multiples.
* Back-emf magnitude and mean torque are not affected by eccentricity, indistinctly for DE or SE. This was observed for all the evaluated slot/pole combinations. However, slot/pole combinations with a low number of evenly distributed phase groups can develop a mild back-emf unbalance.  
The findings of this analysis can be used in the design stage of a MPMSM and aim to enable the inclusion of the sensitiveness of each performance indicator to quickly compare the performance between slot/pole combinations. Furthermore, the observed results for the cogging torque and radial forces can be used for diagnosis ends: in MPMSMs with a slot number close to their pole number, anomalous cogging torque increases can indicate the presence of SE or DE, which can be distinguished by the harmonic order of the cogging torque signal.  
Conceptualization, D.R., C.M., and W.J.; methodology, D.R., W.J., and G.B.; software, D.R. and C.M.; validation, D.R. and C.M.; formal analysis, D.R. and W.J.; investigation, D.R.; resources, W.J., J.R., J.A.T., and G.B.; data curation, D.R. and C.M.; writing-original draft preparation, D.R., C.M., W.J., G.B., and J.R.; writing-review and editing, D.R., W.J., G.B., and J.A.T.; visualization, D.R.; supervision, W.J., J.A.T., and G.B.; project administration, W.J.; funding acquisition, W.J., J.R., and G.B. All authors have read and agreed to the published version of the manuscript.  
This work is supported in part by the Agencia Nacional de Investigacion y Desarrollo (ANID), Chile through grant ANID-PFCHA/Doctorado Nacional/2020-21200350, project FONDECYT REGULAR #1201667, and project FONDEF ID21I10099.  
Not applicable.
## 3 Results and Discussion
### Effect of Catalytic Conditions
#### 3.3.5 Effect of Inulin Concentration  
The effect of the inulin concentration on the hydrolysis reaction was studied experimentally. The hydrolysis results were presented in Figure 9. As shown in Figure 9a, when the amount of inulin concentration increased from 10% to 40%, the growth of hydrolysis ratio was slowed down and it took a longer time for complete hydrolysis of inulin. When the concentration of inulin was lower than 30%, the inulin almost could be completely hydrolyzed in 35 min. The PEK-C-ILs powders catalyst exhibited excellent hydrolysis performance with yields up to 90% under these three kinds of inulin concentration at 25 min. However, when the inulin concentration was more than 30%, the hydrolysis rate of inulin was obviously decreased. The TRS yield at 25 min was only 78.1%. This result can be explained in  
\begin{table}
\begin{tabular}{c c c c} \hline
**PEK-C-ILs** & **A** & **b** & **c** \\ \hline Mean pore size/nm a & 185 & 112 & 71 \\ \hline \end{tabular}  
* Data were measured using the image] software based on the SEM images of Figure 7.  
\end{table}
Table 2: Pore size of PEK-C-ILs powder catalysts.  
Figure 8: Effect of the pore size of the PEK-C-ILs powder catalyst on the TRS of inulin. Hydrolysis conditions: DCM 1.67, inulin concentration 20%,PEK-C-ILs 4 wt %,temperature 65 \({}^{\circ}\)C.  
terms of dissolution mechanism and diffusion mechanism. A higher inulin concentration strongly increases the molecule diffusion resistance, which is not conducive to the process of mass transfer. In addition, the solubility of inulin is about 6-35% under different temperature [31], so the dissolution of inulin with concentration of 40% was reduced, resulting in the hydrolysis rate decreased.  
On the other hand, as shown in Figure 9b, the concentration of reducing sugar increased as the concentration of inulin increased from 10% to 40%. The corresponding reducing sugar concentration was improved from 0.53 mol/L to 1.82 mol/L. Compared to a solution with low concentration of inulin, increasing the inulin concentration caused an increase in density of glycosidic bonds, which enhanced the interaction probability between the active sites of ILs and the glycosidic bonds to a large extent. This behavior could result in a higher yield of reducing sugar. Thus, based on the above analysis, the hydrolysis rate increased with increasing the inulin concentration from 10% to 30%, which improved the utilization efficiency of PEK-C-ILs powder catalyst. And considering economy, a higher initial inulin polysaccharide concentration is more favorable for fermentation solution, since it is desired to get higher ethanol concentration and then decrease the cost of ethanol/water separation in industry application, the appropriate concentration of inulin should be 30%.  
Figure 9: Effect of inulin concentration on the TRS. Hydrolysis conditions: concentration of PEK-C-ILs 4.0 wt %, DCM 1.67, temperature 65 \({}^{\circ}\)C. (**a**) Variation tendency of TRS (**b**) Concentration of reducing sugar.
## 2 Materials and Methods
### IQ Demodulation  
Given a sinusoidal input voltage \(V_{i}\) provided by the BK Precision 4064 into the transmit coil, a sinusoidal output voltage \(V_{o}\) can be read on the receiver coil. In the ideal case, these voltages can be defined as  
\[V_{i}(t)=A_{i}\cos(2\pi ft),\text{ and} \tag{1}\]  
\[V_{o}(t)=A_{o}\cos(2\pi ft+\phi). \tag{2}\]  
The BK 4064 also generates a reference signal  
\[V_{r}(t)=A_{r}\cos(2\pi 4 ft), \tag{3}\]  
which is down-converted by the AD8333 to the quadrature pair  
\[V_{r,I}(t)=A_{r}\cos(2\pi ft),\text{ and} \tag{4a}\] \[V_{r,Q}(t)=A_{r}\cos(2\pi ft+90^{\circ})=-A_{r}\sin(2\pi ft). \tag{4b}\]  
Signals (4a) and (4b) are multiplied with (2), and with the use of product-to-sum trigonometric identifies, one can obtain  
\[V_{o}\left(t\right)\times V_{r,I}(t)=\frac{A_{o}A_{r}}{2}\cos(4\pi ft+\phi)+ \frac{A_{o}A_{r}}{2}\cos(\phi),\text{ and} \tag{5a}\] \[V_{o}(t)\times V_{r,I}(t)=-\frac{A_{o}A_{r}}{2}\sin(4\pi ft+\phi)+\frac{A_{o}A_ {r}}{2}\sin(\phi). \tag{5b}\]  
A low-pass filter removes the high-frequency (2\(f\)) component and thus eliminates the time dependency, providing the commonly known \"I\" and \"Q\" DC signals:  
\[V_{I}=\frac{A_{o}A_{r}}{2}\cos(\phi), \tag{6a}\] \[V_{Q}=\frac{A_{o}A_{r}}{2}\sin(\phi). \tag{6b}\]  
Finally, the complex signal response that is used in this work, \(r\), is defined as  
\[r=V_{I}+jV_{Q}. \tag{7}\]  
where \(j=\sqrt{-1}\) is the imaginary unit. When recorded against changing angle, \(r[n]\) refers to the value of \(r\) at the \(n\)th angle measurement. After compensating for scaling and the reference signal amplitude \(A_{r}\), this signal relates the magnitude \(A_{o}\) and phase \(\phi\) from the physical phenomena by  
\[A_{o}=|r|=\sqrt{V_{I}^{2}+V_{Q}^{2}},\text{ and} \tag{8a}\]  
Figure 3: Signal processing flow for ECT system.  
\[\phi=\angle r=\tan^{-1}\frac{V_{Q}}{V_{I}}. \tag{8b}\]
## 3 Experimental Verification
### Discussion
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Length/Rotating Speed** & **1 A\(\rightarrow\)0.5 A** & **1 A\(\rightarrow\)0.3 A** & **0.5 A\(\rightarrow\)0.3 A** & **0.3 A\(\rightarrow\)0.5 A** & **0.3 A\(\rightarrow\)1 A** & **0.5 A\(\rightarrow\)1 A** & **Average** \\ \hline
1024/30 Hz & 44.71 & 37.63 & 34.26 & 32.61 & 29.71 & 27.24 & 34.36 \\
2048/30 Hz & 46.27 & 39.92 & 34.18 & 34.50 & 31.24 & 25.32 & 35.24 \\
4096/30 Hz & 49.10 & 40.33 & 38.77 & 36.67 & 32.22 & 29.36 & 37.74 \\ Average & 46.69 & 39.29 & 35.74 & 34.59 & 31.06 & 27.31 & 35.78 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Load adaptability test results. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Length/Load** & **40 Hz\(\rightarrow\)30 Hz** & **40 Hz\(\rightarrow\)20 Hz** & **30 Hz\(\rightarrow\)20 Hz** & **20 Hz\(\rightarrow\)30 Hz** & **20 Hz\(\rightarrow\)40 Hz** & **30 Hz\(\rightarrow\)40 Hz** & **Average** \\ \hline
1024/1 A & 41.37 & 39.28 & 46.36 & 38.14 & 33.44 & 36.10 & 39.12 \\
2048/1 A & 48.93 & 44.88 & 51.21 & 39.62 & 43.27 & 39.19 & 44.52 \\
4096/1 A & 54.31 & 49.37 & 42.53 & 43.20 & 45.12 & 43.18 & 46.29 \\ Average & 48.20 & 44.51 & 46.70 & 40.32 & 40.61 & 39.49 & 43.31 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Rotating speed adaptability test results. Figure 14: Comparative analysis of DNNs adaptability.
# Vulnerability Analysis of LTE-R Train-to-Ground Communication Time Synchronization
## 5 Vulnerability Analysis of LTE-R Time Synchronization
### Vulnerability Analysis  
During LTE-R time synchronization, a large number of malicious attacks occur during the message interaction process between the master and slave clocks, especially when waiting to receive critical time synchronization messages [18]. Based on this, this paper takes all the time spent waiting to receive time synchronization messages in the time synchronization process as the vulnerable nodes. These nodes can affect the vulnerability of the LTE-R time synchronization process, as shown in Table 3.  
Figure 6: MC is isomorphic with the SPN model.  
In Table 3, \(\lambda_{4}\), \(\lambda_{5}\), and \(\lambda_{13}\) are used as the average firing rates of receiving key PTP messages, and their valuesare determined by the attacker who successfully intercepted the message. By changing the average firing rate value \(\lambda_{i}\), the operation of the attacker can be simulated and the relationship with the steady-state probability \(P(M_{i})\) value of the protocol exception and normal end state can be established through Equation (6).Through simulation experiments, we find that when the average firing rate \(\lambda_{i}\) is greater than 30, the steady-state probability \(P(M_{i})\) value of each end state remains unchanged, which means that the \(P(M_{i})\) value of each state tends to be stable when \(\lambda_{i}\) is 30. Therefore, we choose to simulate the operation of the attacker by changing the average firing rate \(\lambda_{i}\) in the range of 0-30. Moreover, we establish the relationship between the different attack behaviors of the attacker and the steady-state probabilities \(P(M_{i})\) of the abnormal and normal states of the protocol through Equation (6).  
The \(P(M_{i})\) value of the abnormal and normal end states of the clock nodes is set as the index to measure the vulnerability of the synchronization process. At that time, the smaller the \(P(M_{i})\) value of the abnormal end state and the larger the \(P(M_{i})\) value of the normal end state, the stronger the survivability of the clock node in the attack state and the more robust the time synchronization network protocol and vice versa. This index is used to study the impact of the firing rate change of each vulnerable node on the vulnerability of the LTE-R time synchronization network protocol.
# Mass Collaboration and Learning: Opportunities, Challenges, and Influential Factors
## 4 Analysis of Affecting Factors
### Quality of Knowledge Building and Learning
#### 4.5.1 Evaluating the Quality of Generated Knowledge  
Undoubtedly, it is vital in this new context to be able to evaluate how much trustworthy the acquired knowledge is, because the knowledge is power, and it serves as a basis for making choices and decisions, and also understanding the world. Naturally unreliable knowledge may lead to failure at individual and collective level. Reliability refers to believability of knowledge and its source [126]. Evaluating the quality and reliability of generated knowledge is a multidimensional challenge by its nature, and has turned into a central challenge in various fields of study, e.g., organization management [127], web information system [128], etc.  
Various research works have been conducted from different perspective to find practical ways for evaluating the quality of knowledge. For instance, regarding the reliability of online contents, a number of questions can provide some guidelines for this evaluation:  
1. [label=(0)]
2. Who is the author or publisher (individual or organization)? * Does the author or publisher have high expertise with good qualifications and reputation? * Can they be contacted for discussion or clarification?
3. What can be said about the structure, style, context, content, and completeness of the knowledge that is provided by the author? * What is implied by the content? * Are there any evidences that support it?
4. When was the knowledge published? * Is it up to date? * Is a publication and expiration date provided?
5. Where else can the provided knowledge be found? * Is the knowledge authentic? * Is the piece of knowledge original or was it copied?
6. Why was the provided knowledge published? * What are the biases, assumptions, perspectives and opinions of the author? * Who are the intended audiences for the published knowledge?  
Furthermore, [129] introduces two different ways of quality evaluation (local and global measuring) as a part of the information fusion system; [130] offers a contextual model of web site evaluation (that focuses on information external to a particular site); [131] recommends a checklist model that focuses on assessing the internal characteristics of web sites (e.g., author identification, checking last update,etc.). The literature shows that many researchers, (e.g., [2; 130; 132; 133]) do concur that for evaluating the quality of generated knowledge, learners need to critically take into account some classic criteria that are listed in Table 13.