esa-sceva/satcom-chunk-collection huggingface dataset:
# Quantum Computing Approaches for Mission Covering Optimization
## 4 Algorithm Implementation
### Scenario 1 (One Constraint)
#### 4.1.1 QA and QAOA
If \(f_{obj}(x)\) is the objective function to be minimized, the Lagrangian function is  
\[\mathcal{L}(x,\lambda)=f_{obj}(x)+\lambda\cdot\mathsf{CONSTR}(x). \tag{10}\]  
The solution to the original constrained problem is always a saddle point of this function. Setting a large value for \(\lambda\), the term related to the constraint, will have the greatest impact on the optimization problem. The solution will minimize the constraint first and then the cost. The new objective function that includes the constraints is:  
\[ \begin{split} f_{obj}(x)&=\mathcal{L}(x,\lambda) \\ =\sum&{}_{m\in\mathbf{M}}\mathsf{MC}(x,m)+\frac{1}{| \mathbf{R}|}\sum_{r\in\mathbf{R}}\mathsf{PC}(x,r)\\ &\quad+\lambda\cdot\sum_{r\in\mathbf{R}}\mathsf{CONSTR}(x,r). \end{split}  \tag{11}\]  
QAOA for this method uses an equal superposition for the starting state \(|\Psi\rangle\) over \(N\) states:  
\[|\Psi\rangle=\frac{1}{\sqrt{N}}\sum_{i=0}^{N-1}|i\rangle. \tag{12}\]  
The value \(N\) is equal to \(2^{n}\) where \(n\) is the number of qubits used. For this problem, the number of qubits used is \(N_{M}\cdot M_{R}\), and the number of missions times the number of resources. The mixing operator is constructed using a Hamiltonian, which is the sum of Pauli-X as follows:  
\[X_{i}= \begin{array}{ccccc}I&\otimes\cdots\otimes&X&\otimes\cdots\otimes&I,\\ 1&&i&&n\\ \end{array}  \tag{13}\]  
\[H_{M}=\sum_{i=1}^{n}X_{i}. \tag{14}\]
# Analysis of Low Cost Communication Technologies for V2I Applications
###### Abstract  
The automated and connected vehicle will be a great technology development and it will change mobility habits. The two main positive effects of its integration are the improvement of road safety and the reduction of pollutant emissions of the vehicles. But first, the technology must be available. With the arrival of 5G (Fifth Generation), it will be a reality. However, the 5G could have some operation failures which could isolate the vehicle from the rest of the infrastructure. So, a solution is required which can improve communication reliability such that, if the 5G would fail, the short/middle range technology integrated will lead the vehicle with V2I communication. This integration would provide a reliable and strong solution. In this work, an analysis of different available communication technologies was carried out with a short/middle range, the selection criteria being lower cost and easy integration with 5G. To contrast the technologies, a validation methodology was developed, which enabled us to evaluate the performance of V2I applications. We observed a comparatively higher performance of the module nRF24L01+ for V2I communication.  
V2I; nRF24L01+; ZigBee; Wi-Fi; communicative performance; low cost +
Footnote †: journal: Applied Physics Letters  
_Article_
## 4 Acoustic Emissions (AEs) of Fissured Sandstone during the Compression Process
### Initial Cracking during the Compression Process  
The consideration of the initial crack stress and time is crucial for comprehending the phenomenon of initial cracking during the compression of fissured sandstone. When subjected to axial compression, the tip of the fissure fractures, giving rise to an initial crack. The stress sustained by the sandstone at this moment is defined as the initial crack stress, while the corresponding time is referred to as the initial crack time. The first peak in the AE event corresponds to both the initial crack stress and time during the compression process. Figure 8 illustrates that there is an increase in both initial crack stress and time  
Figure 7: AE events and axial strain in dried, saturated, and frozen-saturated states.  
with increasing inclination angle in all three states. In a dried state, there is a slight decrease followed by a gradual increase in initial crack stress as inclination angle rises; similarly, the curve for initial crack time exhibits a similar trend to that of initial crack stress. For both saturated and frozen-saturated states, there is a proportional increase in both initial crack stress and time with inclination angle. The ranking order for these parameters at a specific inclination angle can be stated as follows: frozen-saturated state > dried state > saturated state. This implies that the softening effect of pore water and the enhancement due to freezing temperature also influence the initiation of cracks in fissured sandstone.  
The enhancement rate \(F\) is defined as the ratio of the initial crack stress to UCS. This parameter can aid in understanding the relationship between initial crack stress and inclination, and its equation is as follows:  
\[F=\frac{R_{i}}{R_{p}}\times 100\% \tag{1}\]  
where \(R_{i}\) is the initial crack stress of the fissured sandstone and \(R_{p}\) is the UCS of fissured sandstone. The data presented in Figure 9 illustrate the relationship between F and inclination angle across three states. It is evident that F increases with rising inclination angle in both the saturated and frozen-saturated states, indicating a gradual approach between the initial crack stress and the UCS, and an increased difficulty in initial cracking as inclination rises. This can be attributed to the fact that higher inclination angles impede strain localization near fissures, resulting in a reduced deformation likelihood. Conversely, the enhancement rate F remains constant at 20% for the dried state regardless of changes in inclination angle. Furthermore, it should be noted that the pore water (ice) enhances the ductility of fissured sandstone while also improving its resistance against fractures.  
Figure 8: Initial crack stress and time at different inclination angles.
# Emergence of White Organic Light-Emitting Diodes Based on Thermally Activated Delayed Fluorescence
## 3 Approaches for WOLEDs Based on TADF
### WOLEDs Based on TADF and Conventional Fluorescence
#### 3.3.5. Single-EML WOLEDs Comprising TADF Host and Fluorescence Dopants  
Due to the simplified characteristic, another solution to realize single-EML WOLED is the use of TADF host and fluorescence dopants. For this solution, the white emission is originated from the fluorescence dopants, while the TADF host mainly functions as a triplet harvester. Besides,  
Figure 7: Schematic diagram showing the energy transfer process for maximum quantum efficiency. Reproduced with permission from [137], Elsevier, 2015.  
the concentration of both the blue and complementary color fluorescence dopants is very low, which can reduce the charge trapping and Dexter energy transfer by the fluorescent dopants.  
[PERSON] et al. described this approach by codoping a blue fluorescence emitter and a yellow fluorescence emitter into a TADF host, obtaining a maximum EQE of 14.0% and PE of 36.2 lm W\({}^{-1}\)[138]. To develop the high-efficiency WOLED, they first explore a blue OLED with the structure of ITO (120 nm)/PEDOT:PSS (60 nm)/mCP (30 nm)/10-(4-((4-(9H-carbazol-9-yl)phenyl)sulfonyl)-phenyl)-9,9-dimethyl-9,10-dihydroacridine (CzAcSF): 0.3% 2,5,8,11-tetra-tert-butylperylene (TBPe) (25 nm)/TSPO1 (5 nm)/TPBI (30 nm)/LiF (1 nm)/Al (200 nm), achieving a maximum EQE of 15.4%. For this blue OLED, \(\sim\)100% IQE can be realized assuming that all triplet excitons are harvested by the RISC process, as shown in Figure 8. In this blue system, efficient Forster energy can transfer from CzAcSF to TBPe, while little charge trapping by TBPe and little Dexter energy transfers from CzAcSF to TBPe due to the very low concentration of 0.3% TBPe. After the demonstration of the blue device, a single-EML WOLED has been developed. The architecture of the WOLED comprises the EML of CzAcSF: 0.3% TBPe: 0.4% 2,8-ditertbutyl-5,11-bis(4-tert-butylphenyl)-6,12-diphenyltetracene (TBRb, 25 nm), while other layers are same as those of the blue OLED. By using a low concentration of TBRb (0.4%), a pure white color of (0.31, 0.37) is obtained.
# Co-Simulation of Multiple Vehicle Routing Problem Models
## 4 Implementation and Results
### Co-Simulation of VRP Multi-Model  
In this section, we run different forms of combined models and perceive the improvement provided by their co-simulation. In order to develop interactive VRP multi-models, we use MECSYCO which offers multiple integrating VRP models by defining the input and output port of coupling artefact. VRP instances [29] are a set of 100 instances created to offer a more universal and stable experimental setting.  
Experiments were carried out in order to analyze the performance of the proposed VRP multi-model. The main objective is to assess whether the co-simulation has a direct impact on the qualitative performance of the obtained results. In this context, three composition are proposed for the interaction between the VRP multi-model used in the experiments:  
* Coupling two different VRP models: \(M_{1}\) with \(M_{2}\).
* Coupling two same VRP models: \(M_{1}\) with \(M_{1}\).
* Coupling two same VRP models: \(M_{2}\) with \(M_{2}\).  
Tables 3-5 show the result of VRP co-simulation where:  
* Symbol A means: after co-simulation;
* Symbol B means: before co-simulation;
* Perc-Dev B is the percentage deviation of single model before co-simulation;
* Perc-Dev A is the percentage deviation after co-simulation for two models in interaction;
* Processing time B (s) is the processing time in second for just one model before co-simulation;
* Processing time A (ms) is the processing time in milliseconds after co-simulation for two models in interaction.  
Table 3 presents the co-simulation results of model \(M_{1}\) with \(M_{1}\) which demonstrate enhanced performance of the found solution in terms of percentage deviation and processing time compared with the execution of single model \(M_{1}\).  
Table 4 shows the result of the combination of the two same models \(M_{2}\) with \(M_{2}\). We perceive that there is an improvement in the found solution compared with one model \(M_{2}\) in both the solution cost and the time of processing.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Inst.** & **BKS** & **Model 2** & **Per-Dev \%** & **Processing Time (s)** \\ \hline A-n32-k5 & 784 & 807 & 2.85 & 19.241 \\ A-n33-k5 & 661 & 661 & 0 & 38.84 \\ A-n33-k6 & 742 & 757 & 1.98 & 16.82 \\ A-n60-k9 & 1408 & 1491 & 5.56 & 90.83 \\ B-n78-k10 & 1266 & 1318 & 3.94 & 1043.46 \\ \hline \hline \end{tabular}
\end{table}
Table 2: VRP result of \(M_{2}\).  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Inst.** & **Per-Dev B \%** & **Per-Dev A \%** & **Processing Time B (s)** & **Processing Time A (ms)** \\ \hline A-n32-k5 & 1.25 & 0.63 & 16.26 & 381 \\ A-n33-k5 & 0 & 0 & 26.46 & 377 \\ A-n33-k6 & 2.23 & 1.32 & 11.98 & 160 \\ A-n60-k9 & 2.35 & 1.53 & 91.18 & 162 \\ B-n78-k10 & 4.95 & 2.98 & 112.18 & 739 \\ \hline \hline \end{tabular}
\end{table}
Table 3: The obtained co-simulation result of models \(M_{1}\) with \(M_{1}\).
## 6 Conclusions  
In this paper, we propose a new hardware security architecture consisting of a memristor-based PUF and Bloom filters to improve security. In our proposed structure, two different types of Bloom filters are used, the PDBF and CRPBF, that store information about the challenge and response of the authentication server; the structure detects arbitrary challenge attacks and reduces error rates originating from the instability of the PUF. At the front of the configuration, the PDBF identifies whether an input challenge is valid by satisfying two conditions before applying it to pm-PUF directly; one condition is that the challenge is to be included in the CRP table shared by the authentication server, and the other condition is that it should not have been previously used for authentication. When an input challenge turns out to be appropriate, the pm-PUF generates the response corresponding to the input challenge. Next, the result from the PUF is checked by the CRPBF to prevent sending the wrong response to the authentication server. The proposed structure presents a practical solution to remove unnecessary access to PUF by the attack and prevent the reuse of a CRP and detect the wrong PUF response with the error. Moreover, because the data set used to verify the performance of the Bloom filter is circuit-simulated data from the pm-PUF that we proposed in previous work, it is more reasonable and realistic than using arbitrary data from all the theoretical data possibilities.  
Figure 8: Data transmission error rate.  
Figure 9: The number of false positives after deletion.  
The simulation results of the proposed architecture with the Bloom filter show that with use of a small-memory filter, the possible access from attackers decreases, and the used CRPs are mostly deleted. Therefore, the PD-CRP Bloom filter structure proposed in this study can contribute to improving the performance of a hardware-based security system.  
Conceptualization, J.L., and W.S.; software, J.L., and S.C.; investigation, J.L., S.C., D.K., Y.C., and W.S.; writing--original draft preparation, J.L., S.C., D.K., and Y.C.; writing--review and editing, W.S.; project administration, J.L., and W.S.; funding acquisition, J.L., and W.S. All authors have read and agreed to the published version of the manuscript.  
This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (No. NRF-2018R1A6A3A11040736 and NRF-2020R11A1A01065622).  
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
## 2 GNSS RO Event Simulation and Assessment Approaches
### GNSS RO Event Simulation
\tag{5}\]  
where \(r_{TR}\) is the vector from RS to TS, \(r_{TS}\) and \(r_{RS}\) are the position vectors of TS and RS, respectively, \(\hat{n}_{RT}\) is the unit vector along the direction from RS to TS, \(R_{T}\) is the projection of the TS position vector on the RS to TS connecting line, \(r_{TP}\) is the position vector of the occultation tangent point, \((X_{TP},Y_{TP},Z_{TP})\) are the three-dimensional coordinates of the occultation tangent point in the Earth-centered Earth-fixed (ECEF) coordinate system, \(a_{E}\) is the equatorial radius of the Earth, \(e_{E}\) is the first numerical eccentricity of the ellipsoid, \(N\) is the distance from the surface back to the Z-axis intersection along the ellipsoid normal, and \(\phi_{TP}\), \(\lambda_{TP}\), and \(h_{TP}\) are the latitude, longitude, and height of the occultation tangent point in the geodetic coordinate system, respectively, where \(\phi_{TP}\) needs to be solved by iteration. Secondly, we calculated the elevation angle \(E\) and azimuth angle \(A\) of TS relative to the RS running direction. The elevation angle \(E\) and the azimuth angle \(A\) of the TS relative to the RS running direction were defined in a Cartesian coordinate system with the RS mass center as the origin, which were computed by the following formulas [60; 62]:  
\[\left\{ \begin{array}{l}x=v_{RS}\\ y=v_{RS}\times r_{RS}\\ z=x\times y\end{array} \right. \tag{6}\]  
\[\sin E=z\cdot r_{TR}/(\|z\|\cdot\|r_{TR}\|) \tag{7}\]  
\[r_{A}=r_{TR}-\|r_{RT}\|\cdot\sin E\cdot z/\|z\| \tag{8}\]  
\[\cos A=r_{A}\cdot x/(\|r_{A}\|\cdot\|x\|) \tag{9}\]  
where \(v_{RS}\) is the RS velocity vector and \(r_{A}\) is the projection of \(r_{TR}\) in the xy coordinate plane. Finally, we determined whether a GNSS RO event occurred according to the three mathematical criteria of an occultation event and the results of the above two steps. If a GNSS RO event occurred, then we stored its attributes including temporal and spatial data such as RO event ID number, starting and ending time, tangent point latitude, and longitude and height in the occultation table; otherwise, we continued to solve and determine whether an RO event occurred at the next epoch until the end of simulation.
## 3 Results and Discussion
### Effect of Electrodes on the Light Intensity of Plasma Elements  
For low-pressure plasma generators, when a high-frequency DC pulse is used to make the working gas discharge inside the element, the atoms will be then excited by the transferred energy. The excited atoms can lose energy in various ways, one of which is through radiative decay, where the atom releases a photon to transfer energy. The number of photons determines the intensity of the light and is also proportional to the concentration of the plasma. Therefore, the density of the plasma can be qualitatively determined by the intensity of its luminosity [30].  
Figure 6 shows the light intensity of the low-pressure plasma generator measured with both electrodes at the argon gas pressure of 0.5 torr.  
As can be seen, the light intensity of the W electrode is greater than that of the Fe-Ni electrode over the entire range of current, and the light intensity keeps increasing with the increase in current. In comparison, the light intensity of the Fe-Ni electrode decreases when the current exceeds about 150 mA, which verifies that the working condition of Fe-Ni electrode should be below 150 mA, as discussed earlier in Figure 5c.  
This result demonstrates that the W electrode plasma element produces a higher density of plasma under the same conditions, works more reliably, and can withstand a wider range of currents, and the Fe-Ni electrode produced in this paper can work properly within the range of 150 mA.
# Examining Pipe-Borehole Wall Contact and Pullback Loads for Horizontal Directional Drilling
## 2 Analysis of Pipe-Borehole Wall Contact
### HDD Pipe-Borehole Wall Contact Model
#### 2.2.2 Pressure Distribution Exponent in HDD  
The pressure distribution exponent \(n\) determines the distribution form of contact pressure. For internal cylinder contact, Hertz distribution, which has an elliptic form (\(n\) = 1/2), is widely used. The pressure distribution exponent \(n\) can also be obtained through numerical fitting [39]. Considering the limitations of the Hertz model and the complexity of the contact in HDD, using numerical fitting to obtain \(n\) is more suitable  
\begin{table}
\begin{tabular}{c c c} \hline \(\mathbf{A}_{i}\) & **Values** & **Confidence Interval** \\ \hline A\({}_{0}\)/MPa & \(-3.85\times 10^{-3}\) & \([-4.87\times 10^{-3},\)\(-2.84\times 10^{-3}]\) \\ A\({}_{1}\)/1 & \(-1.01\times 10^{-4}\) & \([-1.10\times 10^{-4},\)\(-9.19\times 10^{-5}]\) \\ A\({}_{2}\)/MPa\({}^{-1}\) & \(7.60\times 10^{-7}\) & \([6.38\times 10^{-7},\)\(8.81\times 10^{-7}]\) \\ A\({}_{3}\)/N\(\cdot\)mm\({}^{-3}\) & \(6.21\times 10^{-6}\) & \([5.21\times 10^{-6},\)\(7.22\times 10^{-6}]\) \\ A\({}_{4}\)/N\(\cdot\)mm\({}^{-4}\) & \(-1.15\times 10^{-9}\) & \([-1.56\times 10^{-9},\)\(-7.49\times 10^{-10}]\) \\ A\({}_{5}\)/1 & \(1.52\times 10^{-2}\) & \([1.48\times 10^{-2},\)\(1.55\times 10^{-2}]\) \\ A\({}_{6}\)/MPa\({}^{-1}\) & \(-2.11\times 10^{-3}\) & \([-2.40\times 10^{-3},\)\(-1.82\times 10^{-3}]\) \\ A\({}_{7}\)/mm\({}^{-1}\) & \(6.59\times 10^{-4}\) & \([2.89\times 10^{-4},\)\(1.03\times 10^{-3}]\) \\ A\({}_{8}\)/N\({}^{-1}\) & \(-2.20\times 10^{-5}\) & \([-6.29\times 10^{-5},\)\(1.90\times 10^{-5}]\) \\ \hline \end{tabular}
\end{table}
Table 2: A\({}_{i}\) values and 95% confidence interval.  
Figure 6: Comparison between theoretical and FEM results of the maximum contact pressure \(p_{0}\).  
for HDD pipe-borehole wall contact analysis. The distribution of the contact pressure for 51 different tests is shown in Figure 7. It is evident that the exponential function (Equation (13)) can better describe the distribution of the contact pressure. The value range of the exponent \(n\) in HDD is generally between 0.6 and 0.75.
## 5 Research Trends in Ge Photodetectors
### Normal Incidence to Waveguide Integration  
At the starting stage of Ge-on-Si photodetector development for Si photonics applications, normal incidence Ge photodetectors were first fabricated and comprehensively studied [4; 14; 17; 18; 22; 33; 50; 53; 56-64] due to their ease of processing.  
Due to the bandwidth-efficiency tradeoff, typical NI incidence Ge photodetectors offer moderate quantum efficiencies and bandwidths. Among the reported NI photodetectors, [PERSON] _et al_. [50] reported the highest bandwidth of 49 GHz for Ge-based photodetectors. The Ge p-i-n photodiode was fabricated in Ge grown by MBE two-step Ge growth (Figure 6). Given the nominal Ge intrinsic layer  
Figure 5: Bandwidth and responsivity of selected Ge photodetectors.  
Figure 6: 3D view of the PIN Ge photodiode with 49 GHz bandwidth. From [50].  
thickness of 300 nm, detector diameter of 10 \(\upmu\)m and the series resistance of 25 \(\Omega\), the theoretical bandwidth of 54.3 GHz corresponds well with the experimental value. It should be noted that the reported improved 3 dB frequency of 49 GHz from previous result (39 GHz) [14] is mainly due to the reduced series resistance (Rs) of 15 \(\Omega\) from 32 \(\Omega\). The reported responsivity at 1,550 nm is \(\sim\)0.05 A/W limited by small device footprint and relatively large density of defects in the Ge layer.  
In terms of high responsivity, a thick Ge absorption layer is need. The highest reported value at 1,550 nm wavelength for NI photodetector is 0.75 A/W from a PIN diode with \(\sim\)4 \(\upmu\)m thick Ge layer fabricated and reported by [PERSON] and coworkers [17]. The Ge layer was epitaxially grown on a Si substrate by two-step UHVCVD combined with high temperature cyclic annealling for the reduction of dislocation density. A time response of less than 200 ps and operation \(>\)2.5 Gb/s was also demonstrated.  
The study of the Ge normal incidence photodetectors provides valuable insights into the Ge/Si system and its properties. As the Ge growth technique becomes mature and the particulars of Ge/Si devices have been studied in detail, research has gradually been redirected to the integration of Ge photodetectors on Si waveguides to decouple the tradeoff between bandwidth and efficiency mentioned above. Since Si photonics also require devices to be monolithically integrated on the same Si substrate using an on-wafer optical waveguide, integration of Ge photodetectors with waveguides seems mandatory.  
To date, a number of groups have demonstrated waveguided Ge photodetectors, including MIT [1,23,65-67], IEF [20,40], IME [35,48,54,68,69], INTEL [47,70], IBM [52,55,71] and Kotura [19,72]. Both PIN and MSM structures are reported in these waveguide photodetectors with comparable performance and high speeds of around 40 GBit/s.