esa-sceva/satcom-chunk-collection huggingface dataset:
# High-Speed Tomography--A New Approach to Plasma Bulk Velocity Measurement
## 5 Conclusions  
In this work the plasma bulk velocity of a DC plasma torch was measured non-invasively. For this, a high-speed imaging setup combined with a tomographic acquisition has been presented. The proposed setup observes the measurement object from six directions of view and allows for resolving fluctuations in the plasma plume on the order of microseconds. It also enables the plume to be reconstructed using the ART, and thus the tracking of fluctuations and the calculation of the velocity of these fluctuations, which could be resolved locally in the axial direction. Moreover, the setup provides rough 3D models that visualize the characteristic features of the effluent plasma plume. The calculated velocity results are within the range of values found in other studies. Thus, this diagnostic setup proves to be more than an alternative for measuring velocity as it is non-invasive and provides the temporal characteristic of velocity, as well as a 3D model of the plume that can be used for additional analyses.  
**Author Contributions:** Conceptualization, R.F. and M.J.S.; methodology, R.F.; software, R.F.; validation, R.F.; formal analysis, R.F.; investigation, R.F.; resources, R.F.; data curation, R.F.; writing--original draft preparation, R.F.; writing--review and editing, M.J.S. and J.S.; visualization, R.F.; supervision, J.S.; project administration, R.F.; funding acquisition, J.S. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This work was financially supported by SeRANIS (dtec.bw).  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Data are contained within the article.  
**Acknowledgments:** We acknowledge financial support by Universitat der Bundeswehr Munchen.  
**Conflicts of Interest:** The authors declare no conflict of interest.
# A Novel STDM Watermarking Using Visual Saliency-Based JND Model
## 3 Visual Saliency-Based JND Model
### Luminance Adaptation Effect  
The LA factor remains sensitive to volumetric scaling since the average intensity does not scale linearly with amplitude scaling, so we need the average intensity to scale linearly with volumetric scaling for robustness. We introduce \(\mu_{p}\) to describe the pixel intensity and it is expressed as  
\[\mu_{p}=\frac{\sum\limits_{i=0}^{N-1}\sum\limits_{j=0}^{N-1}I(i,j)}{KN^{2}} \cdot\frac{128}{C_{0}} \tag{10}\]  
where \(N\) is the DCT block size, \(I(i,j)\) is the pixel intensity at the position \((i,j)\) of the block, \(K\) is the maximum pixel intensity, and \(C_{0}\) denotes the mean intensity of the whole image.  
A novel empirical luminance adaptation factor \(M_{LA}\) that employed both the cycles per degree (cpd) \(\omega_{i,j}\) for spatial frequencies and the average intensity value of the block \(\mu_{p}\) can be formulated as  
\[M_{LA}(w_{i,j},\mu_{p})=\left\{\begin{array}{ll}1+(M_{0.1}(w_{i,j})-1)\ |\ \frac{\mu_{p}-0.3}{0.2}\ | ^{0.8}&\mu_{p}\leq 0.3\\ 1+(M_{0.9}(w_{i,j})-1)\ |\ \frac{\mu_{p}-0.3}{0.6}\ |^{0.6}&\mu_{p}>0.3 \end{array}\right. \tag{11}\]  
where the \(M_{0.1}(\omega_{i,j})\) and \(M_{0.9}(\omega_{i,j})\) are empirically set as  
\[\left\{\begin{array}{ll}M_{0.1}(\omega_{i,j})=2.468\times 10^{-4}\omega_{i,j} ^{2}+4.466\times 10^{-3}\omega_{i,j}+1.14\\ M_{0.9}(\omega_{i,j})=1.230\times 10^{-3}\omega_{i,j}^{2}+1.433\times 10^{-2} \omega_{i,j}+1.34\end{array}\right. \tag{12}\]
# Unmanned Aerial Vehicle (UAV) Robot Microwave Imaging Based on Multi-Path Scattering Model
## 4 Results
### The Passive Imaging Results Using Multi-Path Scattering from a Single Tree  
Firstly, the simulation results of a single 5 m high tree located at the position (10 m, 10 m) in the coordinate system is presented and discussed. The height of the flight track of the transmitter and receiver remains unchanged, while the position of the receiver is changed to be at six different zenith angles. The model presented in Section 2 is used to simulate the electric field of this tree at different frequency points from 6 GHz to 6.3 GHz, with a step of 6 MHz and a position from \(-\)500 m to 500 m with a step of 5 m. Next, the simulating electric fields received by UAV robot are processed by the imaging method described in Section 3 to obtain the images. The following six images are obtained by above methods at zenith angles of \(26^{\circ}\), \(36^{\circ}\), \(46^{\circ}\), \(56^{\circ}\), \(66^{\circ}\) and \(76^{\circ}\), respectively, as shown in Figure 4a-f. The scene size is 20 m \(\times\) 20 m, and the size of each pixel is 0.2 m \(\times\) 0.2 m.  
Figure 4: _Cont._From the images, it can be seen that the simulation results demonstrate good performance of the autofocus based on the passive imaging algorithm using multi-path scattering. The energy concentrates on two main parts; the left part is mainly from the direct scattering of the scatterer in the vegetation, and the right part is the summation of a single bounce between the scatterer and the ground. The double bounce of ground-scatterer-ground is too weak to be shown in the images.
## 2 ANFIS Structure  
Fuzzy theory has been widely used in many academic and industrial fields, since it is very effective at solving problems that deal with variables that are difficult to express quantitatively, such as language [14; 18]. In particular, it has mainly been used to solve engineering problems, which pose difficulties in numerical analysis, because of a huge uncertainty of input and output variables and complex interaction mechanisms [19; 20; 21]. In order to predict highly accurate results by means of the fuzzy theory, it is of utmost importance to properly configure fuzzy sets and rules. In this study, as shown in Figure 1, fuzzy rules are configured based on the Sugeno fuzzy model and ANFIS with a back-propagation algorithm for error correction, that is used to more accurately evaluate the effective compressive strengths of the column [22; 23; 24; 25].  
In Figure 1a, \(x\) and \(y\) are the input variables, \(A_{i}\) and \(B_{i}\) are the fuzzy sets of input variables \(x\) and \(y\) corresponding to the \(i\)-th fuzzy rule, \(f_{i}\) is the output variable of the \(i\)-th fuzzy rule, \(a_{i}\), \(b_{i}\) and \(c_{i}\) are the consequent parameters of the \(i\)-th fuzzy rule, and \(f\) is the final result obtained from the defuzzification of \(f_{i}\), where \(a_{i}\), \(b_{i}\) and \(c_{i}\) are calculated using the least-squares estimator. In the ANFIS structure shown in Figure 1b, \(\mu_{A_{i}}\) and \(\mu_{B_{i}}\) are the membership functions of fuzzy sets \(A_{i}\) and \(B_{i}\), and \(w_{i}\) is the \(i\)-th firing strength and represents the membership degree of the \(i\)-th rule, which is the minimum value among the degrees of membership calculated according to the membership functions \(\mu_{A_{i}}\) and \(\mu_{B_{i}}\). When all firing strengths are calculated, the final result (\(f\)) is estimated using the normalized firing strength (\(\overline{w_{i}}\)) and the output variable of the fuzzy rule, where \(\overline{w_{i}}\) is calculated as follows:  
\[\overline{w_{i}}=\frac{w_{i}}{\sum w_{i}} \tag{1}\]  
The error is then calculated by comparing the final result with the experimental data, and generated errors are reduced by means of the backpropagation, as shown in Figure 1b.
# One-Photon-Interference Quantum Secure Direct Communication
## 4 Performance Analysis  
### Comparison with Other QSDC Protocols  
We performed numerical simulations for characterizing the performance of the proposed OPI-QSDC and other QSDC protocols [3; 24]. The key parameter settings for our simulations are shown in Table 1[32; 42].  
As shown in Figure 2, the OPI-QSDC protocol is able to exceed the PLOB bound when \(d>228\) km with practical parameters. The Appendix C contains derivation details of simulation formulas. We also simulate the performance of MDI-QSDC [24] and DL04 [3] protocol with the method of INCUM [26]. The MDI-QSDC and DL04 protocols are two-way protocols which suffer double channel loss over a certain transmission distance. To be more precise, the MDI-QSDC protocol detects twice to complete the transmission of information, while DL04 protocol detects only once. Therefore, the explicit secrecy rate equations used to draw the idealized protocol performance in Figure 2 are:  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Parameter** & **Value** & **Description** \\ \hline \(\zeta\) & 0.2 dB/km & the attenuation coefficient \\ \(\eta_{d}\) & 15\% & the efficiency of detectors \\ \(p_{d}\) & \(8\times 10^{-8}\) & the probability of dark count \\ \(\delta\) & 1.5\% & the misalignment probability \\ \(f\) & 1.2 & the inefficiency function for forward coding \\ \(u\) & 0.046 & the light intensity \\ \hline \hline \end{tabular}
\end{table}
Table 1: Key parameter settings of simulation.  
Figure 2: **Secrecy rate \(log_{10}(R)\) versus the transmission distance of OPI-QSDC and other QSDC protocols.** The black line is the PLOB bound. The green, blue, and red line represent OPI-QSDC, DL04 and MDI-QSDC protocol, respectively. The solid (dashed) lines indicate the parameterized (idealized) protocol performance. For the specific parameters, the rate of OPI-QSDC surpasses the PLOB bound when \(d>228\) km. The longest transmission distance of our protocol is able to achieve 440 km.  
\[\begin{split}& R_{PLOB}^{ideal}=-\log_{2}(1-\eta_{c}),\\ & R_{GPI-QSDC}^{ideal}=\eta_{d}\sqrt{\eta_{c}},\\ & R_{DL04}^{ideal}=\eta_{d}\eta_{c}^{2},\\ & R_{MDI-QSDC}^{ideal}=(\eta_{d}\eta_{c})^{2},\end{split} \tag{7}\]  
where \(\eta_{d}\), \(\eta_{c}\) are the detection efficiencies and the channel losses function, respectively. The DL04 protocol's beginning rates will be higher than the OPI-QSDC, since we did not account for the effects of real light sources on its performance when we parameterized the protocols. The Appendix D contains further simulation details of the DL04 and MDI-QSDC protocols.
# 3D Photoacoustic Tomography System Based on Full-View Illumination and Ultrasound Detection
## 3 Results  
### Performance Test of the 3D-PACT  
#### 3.1.1 Feasibility Verification of Quartz Bowl in the System  
First of all, the photoacoustic experiments were carried out in the ultrasonic transmission mode and ultrasonic reflection mode to verify the feasibility of the quartz bowl. The schematic diagrams of the two experimental devices are shown in Figure 4a,b, respectively. Black tape was selected as the target due to the strong laser absorption. The energy at the fiber exit was around 100 \(\upmu\)J. The energy E in Table 1 refers to the laser energy of the imaging target surface.  
The ultrasonic reflection efficiency \(H\) of the quartz bowl is defined as the ratio of the photoacoustic signal amplitude in the above two signal acceptance modes in the research. The specific expression is:  
\[H=G_{ref}/G_{trm} \tag{6}\]  
Figure 4: (**a**) Schematic diagram of photoacoustic imaging device in ultrasonic transmission mode.  
(**b**) Schematic diagram of photoacoustic imaging device in ultrasonic reflection mode.  
Figure 3: (**a**) A 2D schematic of the improved back-projection reconstruction algorithm, and (**b**) 3D photoacoustic image reconstruction.  
where \(G_{r\!r\!f}\) is the signal amplitude per microjoule laser energy in the ultrasonic reflection mode and \(G_{t\!r\!f}\) is the signal amplitude per microjoule laser energy in the ultrasonic transmission mode. Furthermore, \(G_{t\!r\!f}\) was about 0.01232 V/uJ, found by analyzing the photoacoustic signal obtained from photoacoustic experiment in ultrasonic transmission mode. The quartz bowl was divided into eight areas (Q\({}_{1}\)-Q\({}_{8}\)), and the quartz bowl's ultrasonic reflection efficiency was tested after subtracting the light attenuation of each area.  
The ultrasonic reflection efficiency of quartz bowl was between 198.70% and 204.71%, which could be seen by noting that the amplitude of the photoacoustic signal was nearly doubled in ultrasonic reflection mode. Experiments showed that the quartz bowl used in the system had a higher efficiency of ultrasonic signal reflection, which was helpful for the collection of photoacoustic signals in PACT.
# Application of Terminal Audio Mixing in Multi-Bandwidth End-to-End Encrypted Voice Conference +
## 2 Homomorphic Encryption
### Decryption and Audio Reconstruction  
The server then transmits the mixed ciphertext back to all users, where it is decrypted into plaintext audio data 110110100110011100100111101 in the user's devices. The decrypted big integer is segmented back into individual samples based on the bit length of each sample, including the overflow buffer code. The result is [110110100, 110011100, 10011101].  
Figure 2: Homomorphic decryption process.
# Density Self-Adaptive Hybrid Clustering Routing Protocol for Wireless Sensor Networks
## 3 The Design of DAHC Protocol
### Overall Operation of DAHC Protocol  
Similar to other clustering protocols, the operation of DAHC in each round can be separated into the setup phase and the communication phase. During the setup phase, CHs are chosen by the relevant method. First of all, we introduce the concept of epoch. In the WSNs, if the proportion of the CHs in all nodes is \(P\), then \(1/P\) is an epoch. When the CH is selected by the centralized control method, the CH will do the corresponding calculation work and make preparations for the next election. In a centralized strategy, the energy consumption includes the communication between nodes and the BS and the cost of member nodes joining the cluster each round. When using a distributed method, the nodes will generate CHs according to the calculated information of the first round of the epoch, judge the cluster density in the final stage of clustering, and make the corresponding adjusting operation. In this method, the energy consumption contains the communication between nodes and the BS at the first round of the epoch, and the cost of member nodes joining to cluster each round. In the rest of the rounds of an epoch, the forming cluster dissipates more energy because it has twice as many interactions with the CH than the centralized method. However, the cost of more interactions is much less than the communication with the BS due to the shorter distance. After the formation of the cluster, it enters a stable data communication phase. In this phase, each CH will allocate a TDMA schedule.  
Thus, the member nodes send data to the CH during the corresponding time slot and stay asleep at other times. After the aggregation of received data packets, the CHs will send the results to the BS. After a given time spent on the communication, the network goes into the next cycle until the end of the network lifetime. The flow chart of the DAHC protocol is shown in Figure 1:
# Connectivity Analysis in VANETs with Dynamic Ranges
## 3 Analytical Procedure
### Single-Hop Inter-Vehicle Distance  
#### 3.4.1 Free-Flow Traffic  
In this model, for a Poisson point process distributed \(N\) vehicles in the network with rates \(\lambda(vehs/sec)\) in a road section of length \(L\) are shown to be displaced independently given their individual velocities [30]. Moreover, the distance between any two adjacent vehicles is exponentially distributed and used typically in numerous literature on analyses of connectivity. This distance, \(D\)'s distribution PDF is: \(f_{D}(x)=\rho e^{-\rho x}\), where \(\rho=\frac{\lambda}{\mathbb{E}[V]}(vehs/m)\). To study realistic vehicle traffic, a component of safety distance \(s\) used to cater to the minimum acceptable distance of separation of vehicles and analyse connectivity of vehicles [31]. Authors in [13] use this modified version of separation distance (known as HRPPP) by incorporating \(s\) to study big vehicle shadowing effect in a multi-lane highway. The truncated exponential adjacent distance distribution PDF is;  
\[f_{D}(x)=\begin{cases}\rho e^{\rho(x-s)},&\text{ if }x\geq s>0\\ 0\,&\text{ otherwise;}\end{cases} \tag{27}\]  
whose exact expectation and variance are given by;  
\[\mathbb{E}[D]=\frac{e^{gs}}{\rho}\approx\frac{1}{\rho}\text{ and }\mathbb{V}ar[D]=\frac{e^{gs}(2-e^{gs})}{\rho^{2}}\approx\frac{1}{\rho^{2}}, \text{ as }s\to 0,\]  
where \(\rho=\frac{\lambda}{\mathbb{E}[V]}\), and \(\mathbb{E}[V]\) is vehicles mean velocity.
## 6 Experimental Results  
### System Configuration  
The LPS _LOSNUS_ system is installed in a 4 \(\times\) 6 \(\times\)4 m testing room. The room closely reassembles a standard office room including tables, chairs and other instruments. The system can tolerate a single  
Figure 10: Simulation Results: (**a**) Effect of receiver motion with 0 ms interface spacing (only possible in CDMA system), (**b**) Effect of receiver motion with 10 ms interframe spacing suitable for LPS _LOSNUS_ with up to 3.4 m minimal spacing between consecutively firing transmitters.  
ToA error and includes six transmitters and up to eight receivers. The transmitters used are Senscomp 600 environmental grade electrostatic transducers with a large bandwidth and good acoustic coupling to air due to their low acoustic impedance. At the test system, these transmitters are mounted on the wall and their positions relative to the system of coordinates are marked in Figure 11a. Transmitters can be adjusted in two directions as shown in Figure 11b. All transmitters are wired to an activation unit controlled by a PC with a NI-DAQ card containing digital outputs for selecting the corresponding transmitter and an arbitrary waveform generator (AWG) shown in Figure 12. A high voltage (HV) amplifier amplifies the AWG output.  
Figure 11: **(a)** Test system configuration consisting of six US transmitters. **(b)** Ultrasonic transmitter adjustable in two direction including wiring.  
Figure 12: Activation unit consisting of high voltage (HV) amplifier, demultiplexer and cabling.  
The receivers for calibration and verification are positioned on the opposite side with a distance of approx. 3 to 4 m. A linear moving axis with a length of 1.5 m mounted at a height of approx. 1 m enables tests with moving devices and can be used for judging the quality of the localization and the calibration. The setup for the linear belt including the receiver is shown in Figure 13. The outputs of the receivers are also wired to the NI-DAQ card through a mixer module, which can be used to extend the number of channels to eight. For practical use of the LPS, small embedded sensor nodes and low cost devices were also built by the authors. They deliver the same performance but aim at reducing costs and size of sensor nodes.
###### Abstract
Nanostructures of various shapes--trigonal, nanorods, nanoribbons, hexagonal prism, nanoplates, nanotubes, and spheres--are obtained from selenium [13; 14; 15; 16]. The production of 1D selenium nanorods using various chemical polymers as shaping agents has been commonly reported [17]; nevertheless, the selenium nanorods obtained in this way become unsuitable for use in biological systems. The shape of nanoparticles can influence biological effects. It has been shown that cerium nanorods are able to circulate in the blood for a longer time. It should be noted that the degradation of nanorods occurs much faster than that of spherical nanoparticles due to their larger specific surface area. Moreover, nanorods are less prone to aggregation [18]. Due to the fact that nanoparticles in the form of nanorods are able to remain in the organism for longer periods of time and release large concentrations of selenium into cells, there is no doubt that the mechanism of action of selenium in the form of nanorods needs to be created and studied. We have created a technology for the production of selenium nanorods that are not toxic to healthy cells, which is characterized by low cost and the possibility of its adaptation to the industrial production of nanoparticles. The comparison of anti-tumor effectiveness of spherical selenium nanoparticles (SeNPs) and selenium nanorods (SeNrs) was the main goal of this study. At the same time, in this research we also focus on the differences in the activation of the Ca\({}^{2+}\) signaling system in human glioblastoma A-172 cells and mouse fibroblasts L-929 and the correlation of an elevated level of calcium ions in the cytosol ([Ca\({}^{2+}\)]] with endoplasmic reticulum stress and the induction of apoptosis.
## 7 Irrigation Suitability of Groundwater
### Irrigation Water Quality Index (IRWQI)  
The results of the proposed indices differed from each other when it came to the irrigation suitability of groundwater. To overcome this complexity, all indices were combined in the IRWQI to clearly determine the irrigation suitability of groundwater. The IRWQI was rated as suitable, good, permissible, doubtful, and unsuitable for irrigation using the quantile classification approach in GIS. The integrated IRWQI estimates show that, in January 2020, about 484 km\({}^{2}\) of the groundwater area was suitable for irrigation, followed by 189 km\({}^{2}\) unsuitable, 28 km\({}^{2}\) good, 21 km\({}^{2}\) doubtful, and 17 km\({}^{2}\) permissible for irrigation. In January 2021, 492 km\({}^{2}\) of groundwater in the study area was suitable for irrigation, followed by 169 km\({}^{2}\) unsuitable, 39 km\({}^{2}\) doubtful, 27 km\({}^{2}\) permissive, and 20 km\({}^{2}\) good categories (Table S4).  
The spatial pattern of the calculated IRWQI is illustrated in Figure 7a,b for January 2020 and January 2021, respectively. The coastal regions of most of the study area were unsuitable to permissive for irrigation during both time periods due to the salinization of groundwater from mixing with seawater and the dissolution of formation salt. The construction of artificial recharge structures, such as recharge pits in existing surface waters, construction of percolation ponds, and farm ponds, will support freshwater recharge in the shallow aquifers of the study area and increase the groundwater levels that can be used for irrigation [65]. In addition, the implementation of flood extraction methods, such as the construction of retention dams and the application of surface water in the ephemeral rivers of the study area, can increase the infiltration of freshwater for groundwater recharge [66; 67].  
Figure 6: [PERSON]’s plot of soil permeability for irrigation water quality.
# Analyses of GLONASS and GPS+GLONASS Precise Positioning Performance in Different Latitude Regions
## 2 Evaluation Methods  
This section describes the methods and metrics of data quality check, the analysis indicators for satellite visibility of different systems, and the positioning strategies of DD network and PPP processing, as well as the evaluation indicator for DD network solutions and PPP solutions.