esa-sceva/satcom-chunk-collection huggingface dataset:
# A Lightweight Blockchain-Based IoT Identity Management Approach
## 5 Results
### Invoke and Query Operations Cost  
The transaction logic that is used in this work is simple and only covers the essential features of registration and authentication functions. Besides, the smart contract developed is not computer-intensive, in order to avoid any complexity, as it affects the operation time. In particular, the authentication transaction needs to fetch information from the registration ledger to match the credentials of the requester, which is the only dependency of the coded smart contract (chaincode).  
In this experiment, we adopt 0.5 MB as a block size for maximizing the throughput of both registration transactions and authentication transactions, executing 100 trials for each action. The average time of registration invocation transactions is 170 (Ms), with a throughput of six transactions per second, as shown in Figure 7. Meanwhile, the average time of query transactions is 52.5 (Ms) with a throughput of 19 transactions per second, as shown in Figure 8. The average time of authentication invocation transactions is 145 (Ms),  
\begin{table}
\begin{tabular}{l l l l l l l} \hline \hline
**Channel** & **PLS (MB)** & **Action** & **Avg (Ms)** & **Min (Ms)** & **Max (Ms)** & **Tps** \\ \hline Registration & 0.5 & Invoke & 170 & 142 & 198 & 6 \\ Registration & 1 & Invoke & 205.5 & 191 & 220 & 5 \\ Registration & 1.7 & Invoke & 255.5 & 243 & 268 & 4 \\ Registration & 0.5 & Query & 52.5 & 41 & 64 & 19 \\ Registration & 1 & Query & 69 & 56 & 82 & 14 \\ Registration & 1.7 & Query & 104.5 & 89 & 120 & 10 \\ \hline Authentication & 0.5 & Invoke & 145 & 129 & 161 & 7 \\ Authentication & 1 & Invoke & 161 & 141 & 182 & 6 \\ Authentication & 1.7 & Invoke & 204.5 & 190 & 219 & 5 \\ Authentication & 0.5 & Query & 49.5 & 41 & 58 & 20 \\ Authentication & 1 & Query & 59.5 & 52 & 67 & 17 \\ Authentication & 1.7 & Query & 85 & 74 & 96 & 12 \\ \hline \hline \end{tabular}
\end{table}
Table 1: The payload size (PLS), transaction action, the average time of the trials, minimum and maximum of the transaction latency, and throughput (transaction per second) for registration and authentication ledgers.  
Figure 6: A payload represents a temperature sensor for registration phase.
# Capability of Advanced Ultrasonic Inspection Technologies for Hydraulic Turbine Runners
## 2 Experimental Procedure  
### Manufacturing Process Description  
Inspection of turbine runner welds is an essential aspect of electric-generator units' in-service reliability [4]. In-service inspection data from installed runners show that fabrication flaws are found in the weld joint near the blade's trailing edge. Flaws were discovered by applying a phased array ultrasonic technique using a small wedge to provide suitable contact on a curved surface and good volumetric coverage with an azimuthal focal law type. Typically, flaws are within 30 mm of the trailing edge and in the weld reinforcement that smooths the stresses at the blade's end. Some flaws were found isolated, but clusters of up to 7 indications were also observed. The presence of flaws at the edge of the blade in the area of high service stress is considered in the current investigation. This area is where the start and stop of welding occurs, and thus it is not surprising to observe in-situ point-like reflectors in the weld reinforcement. A T-joint sample was manufactured in martensitic stainless steel (UNS S41500) in accordance with the manufacturing requirements of turbine runners. The T-joint geometry often mimics a turbine runner's trailing edge, with both edges being 25 mm in thickness. The base plate is 60 mm thick and provides the same ultrasonic path for an inspection performed from the turbine web. The weld cap and blade ends are ground to obtain a smooth finish with a curved radius of 25 mm. The preparation is a J-shape grove with a 3 mm gap between the web and blade. Welding was carried out using a multi-pass FCAW process and EC410 NiMo electrodes (same ultrasonic properties as UNS S41500). The study selected the dimensions of the joint to match a typical turbine runner assembly.Typically, 34 passes are required to fill the joint.
# All-Fiber Hyperparametric Generation Based on a Monolithic Fiber Fabry-Perot Microresonator
[PERSON]  
1 National Laboratory of Solid State Microstructures, School of Electronic Science and Engineering, School of Physics, School of Physics, College of Engineering and Applied Sciences, School of Physics, College of Engineering and Applied Sciences, and Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing 210093, China; [EMAIL_ADDRESS] (K.J. ); [EMAIL_ADDRESS] ([PERSON]); [EMAIL_ADDRESS] ([PERSON]); mf1823034@smail. the requirements on comb processing electronics and is of special interest for applications such like dual-comb spectroscopy. Moreover, the pump light is coupled into these microresonators through the evanescent field typically from bus waveguides, tapered fibers, or prisms. Challenges lie in the fact that such a scheme requires either careful mode field overlap management or sophisticated free-space alignment, which may be unfavorable from a practical applications point of view. In a monolithic fiber microresonator, direct pump light injection through end face coupling can be easily realized with low-cost commercial fiber connectors [19]. Such plug-and-play operation is expected to improve the stability and reduce the size and cost of the entire system. In addition, the quality factor of the fiber microresonator is mainly defined by the diffraction loss at the end faces, considering the negligible propagation loss of optical fiber. Thus, the fiber microresonator is a promising platform for Kerr OFC generation with a small footprint entering a frequency regime more typical of mode-locked lasers. In this work, we demonstrate FWM-based hyperparametric generation in a wide spectral span from a fiber Fabry-Perot (FFP) microresonator. Highly nonlinear fiber (HNLF) is fabricated with fine polishing and a dielectric coating for efficient hyperparametric oscillation. Continuous-wave (cw) pump light is coupled into the FFP microresonator through directly connected ceramic ferrules in a ceramic sleeve, as shown in Figure 1a, with an insertion loss below 0.5 dB. The whole setup is fiber-based and all components, including the tunable laser, polarization controller, erbium-doped fiber amplifier (EDFA), and isolator, are connected by fiber splicing or using fiber connectors. Compared with the conventional evanescent field coupling method, such a configuration greatly simplifies the coupling steps and can well resist external mechanical disturbances coming from the environment. All in all, driven by a cw pump laser, FWM can be generated from our FFP microresonator with a fine spectrum tooth of 667 MHz. With the assistance of stimulated Raman scattering in the FFP microresonator [16; 20; 21], the spectral span is further extended to over 400 nm. It is worth noting that such broadband hyperparametric generation with sub-gigahertz line-to-line frequency separation is rarely achieved in a microresonator due to its propagation-limited Q, as mentioned above.
## 2 Integrated Seat Suspension and MR Damper Model
### Dynamic Model of MR Damper  
The MR damper model has been studied and applied by several researchers in the past. In this work, the Modified Bouc-Wen model of the MR damper is implemented. This model was adopted from [PERSON] and [PERSON] (2018). The force generated by the MR damper depends on the time history of the voltage in the coil of the damper, i.e., the supply voltage, and it also depends on the displacement of the damper, \(z_{r}\):  
\[z_{r}=z_{ss}-z_{s} \tag{10}\]  
The FLST-PID determines the supply voltage \(v\) of the MR damper. The force generated by the MR damper was computed by solving the Modified Bouc-Wen model using the voltage \(v\) and the \(z_{r}\). The MR damper force has been computed by Equation (11):  
\[F_{mr}=c_{1}y+k_{1}(z_{r}-x_{0}) \tag{11}\]  
where, \(k_{1}\) represents the accumulated stiffness as a spring with a constant value \(c_{1}\) and is used to simulate the hysteresis loop at low frequencies.  
\[y=\frac{1}{c_{0}+c_{1}}\{\alpha z+c_{0}x+k_{0}(z_{r}-y)\} \tag{12}\]  
In Equation (12), \(c_{0}\) denotes the damping at the higher velocities. To control the stiffness at the large velocities another spring with the constant \(k_{0}\) was introduced in Equation (12). Furthermore, \(x_{0}\) denotes the initial displacement. The internal moments in the MR damper is signified by Equation (12). The hysteresis loop of the MR damper is presented by \(z\), which is known as the evolutionary variable. The behaviour of the evolutionary variable is governed by Equation (13):  
\[z=-\gamma\big{|}z_{r}-y\big{|}z\big{|}^{n-1}z-\beta(z_{r}-y)\big{|}z\big{|}^{n }+A(z_{r}-y) \tag{13}\]  
The shape of the hysteresis loop can be synchronized by \(\gamma\), \(\beta\), \(n\) and \(A\). The force generated by the MR damper was controlled by the input \(u\). The control input is associated with the amount of voltage supply \(v\) by the following equations, Equations (14)-(17).  
\[\alpha=\alpha(u)=\alpha_{a}+\alpha_{b}u \tag{14}\]  
\[c_{1}=c_{1}(u)=c_{1a}+c_{1b}u \tag{15}\]  
\[c_{0}=c_{0}(u)=c_{0a}+c_{0b}u \tag{16}\]  
\[u=-\eta(u-v) \tag{17}\]  
The effect of the sensor delays is not considered in this work.
## 4 Prediction Performance Analysis
When the spindle speed was 8500 r/min, the _RMSE_ values of the POA-CNN-LSTMNN, CSOA-CNN-LSTMNN, and LSTMNN models were 0.9083 and 0.7241, 1.2877 and 0.9867, 1.5078 and 1.2611, and 2.0011 and 1.6803, respectively: and the \(R^{2}\) and _MSE_ values were 0.9938 and 0.825, 0.9875 and 1.6582, 0.9828 and 2.2734, and 0.9697 and 4.0042, respectively. When the spindle speed was 10,000 r/min, the _RMSE_ values of the POA-CNN-LSTMNN, CSOA-CNN-LSTMNN, CNN-LSTMNN, and LSTMNN models were 0.8078, 1.6685, 2.176, and 3.5479, respectively: the _MAE_ values were 0.6737, 1. 2743, 1.6481, and 2.8598, respectively: the \(R^{2}\) values were 0.9957, 0.9814, 0.9685, and 0.9162, respectively: and the _MSE_ values were 0.6525, 2.7839, 4.7349, and 12.5877, respectively. The average _RMSE_, _MAE_, \(R^{2}\), and _MSE_ values of the POA-CNN-LSTMNN model at different speeds were 0.6383, 0.5259, 0.9936, and 0.4531, respectively. The mean _RMSE_, _MAE_, \(R^{2}\), and _MSE_ values of the CSOA-CNN-LSTMNN model at different speeds were 1.009, 0.7998, 0.9845, and 1.1822, respectively. The average _RMSE_, _MAE_, \(R^{2}\), and _MSE_ values of the CSOA-CNN-LSTMNN model at different speeds were 1.2561, 1.0261, 0.976, and 1.8469, respectively. The mean _RMSE_, _MAE_, \(R^{2}\), and _MSE_  
values of the LSTMNN model at different speeds were 1.9324, 1.5907, 0.9453, and 4.5561, respectively. The POA-CNN-LSTMNN model had 36.7%, 49.2%, and 67% lower average _RMSE_ values than the CSOA-CNN-LSTMNN, CNN-LSTMNN, and LSTMNN models, respectively. The average _MAE_ values of the POA-CNN-LSTMNN model were 34.2%, 48.7%, and 66.9% lower than those of the CSOA-CNN-LSTMNN, CNN-LSTMNN, and LSTMNN models, respectively. Compared to the CSOA-CNN-LSTMNN, CNN-LSTMNN, and LSTMNN models, the average \(R^{2}\) and _MSE_ values of the POA-CNN-LSTMNN model increased by 0.9%, 1.8%, and 5.1% and decreased by 61.7%, 75.5%, and 90%, respectively. To sum up, the POA-CNN-LSTMNN model outperformed other models across all evaluated index values. This suggests that the model exhibited superior prediction performance and delivered the best forecasting results. Figure 25: Values of four evaluation indexes for each model at different speeds: (**a**) 1000 r/min: (**b**) 2500 r/min: (**c**) 4000 r/min: (**d**) 7000 r/min: (**e**) 8500 r/min: (**f**) 10,000 r/min.
## 2 Design Methodology for Integrated Signal
### OFDM Chirp Signal Based on LDPC Coding  
Low-density parity-check (LDPC) codes have become the preferred channel coding scheme for wireless communication standards such as IEEE802.16e and 5G [23] because of their error-correcting performance that approaches the Shannon limit [23]. In this integrated system, some consecutive subcarriers may undergo deep fading [20]. Therefore, this paper introduces LDPC coding to address the random errors caused by deep fading in a multi-carrier scenario. The LDPC code \(v\) is a set of linear packet codes \((n,k)\), where \(n\) is the code length and \(k\) is the length of the message sequence, which can be uniquely determined by a sparse check matrix \(H\). Each row of the checksum matrix corresponds to a checksum equation, and each column corresponds to a variable node. The LDPC encoder adds redundancy to the data based on the LDPC checksum matrix to enhance the error correction of the signal [23; 24].  
Additionally, we chose an LDPC code rate of 1/2 to enhance the error correction performance of the signal. The error correction capability of LDPC codes is closely tied to their code rate. For LDPC codes with a code rate of 1/2, the error correction performance is more robust under the same codeword length. Additionally, the use of a lower code rate can reduce the complexity of decoding, making it suitable for communication systems with constrained resources. Some communication standards and protocols have adopted the design of LDPC codes with a rate of 1/2, such as the Wi-Fi standard, enhancing compatibility between devices and improving the interoperability of communication systems.  
Figure 3 represents a block diagram of the OFDM chirp transceiver system design based on LDPC coding. The communication information is LDPC-coded in the form of a bit stream [25; 26]. To enhance communication efficiency, every four bits of encoded data are converted to decimal for \(16-QAM\) modulation. After inserting VC into the communication signal, it undergoes odd-even subcarrier modulation using OFDM, along with the chirp signal sampled in the frequency domain, to generate multiple integrated symbols. The CP is then inserted between symbols to obtain the integrated signal. At the receiving end, upon receiving the integrated signal carrying channel information, the signal is subjected to orthogonal demodulation. In communication signal processing, the radar signal can be treated as pilot information inserted at a 1:1 ratio for channel estimation. This, along with the parameters obtained from timing synchronization, is used for channel equalization, resulting in more accurate communication data. In radar signal processing, joint super-resolution estimation of radar target range and velocity is achieved using matched filtering and pulse compression.  
Figure 3: Steps in integrated signal design and processing.
## 3 Results and Discussion
### SEM Study  
SEM assessments were performed after the potentiodynamic polarization of the annealed and ECAP samples in the 3.5 wt % NaCl solution. Figure 9 shows SEM micrographs indicating evidently limited degradation due to corrosion, especially on the three passes of the ECAP sample test. Figure 9 displays moderately little, semi-circular pits of various dimensions developed all through the non-deformed material surface. The number of pitting attacks increased due to the ECAP process.  
\begin{table}
\begin{tabular}{l c c c c c c} \hline \hline
**Sample** & \(R_{s}\) **(\(\Omega\) cm\({}^{2}\))** &
\begin{tabular}{c} _CPE_ \\ **(uF. Cm\({}^{-2}\)S(n-1))** \\ \end{tabular} & \(n\)** & \(R_{ct}\) **(\(\Omega\) cm\({}^{2}\))** & \(R_{L}\) **(\(\Omega\) cm\({}^{2}\))** & \(L\) **(H cm\({}^{-2}\))** \\ \hline As-received & 24.67 & 29.4 & 0.95 & \(23.67\times 10^{2}\) & 2127 & 1873 \\ First pass & 20.74 & 33.3 & 0.90 & \(20.84\times 10^{2}\) & 448 & 365 \\ Second pass & 23.44 & 48.6 & 0.85 & \(19.44\times 10^{2}\) & 302 & 213 \\ Third pass & 22.96 & 50.4 & 0.80 & \(15.46\times 10^{2}\) & 182 & 115 \\ \hline \hline \end{tabular} Note: \(R_{s}\), \(R_{ct}\), _CPE_, \(L\), \(n\) and \(R_{L}\), which symbolize the solution resistance, charge transfer resistance, constant phase element, inductance element, parameter measures the perfection of this element (varying between 0 and 1) and electrical inductance, respectively.  
\end{table}
Table 2: Electrochemical impedance spectroscopy results in the 3.5% NaCl Solution.  
Figure 7: Equivalent potential circuit for the fitted model.  
A much bigger and profound rectangular pit occurred after three passes. This attack happened in the interface between the particles and the Al lattice. In the current work, the tendency to be attacked by corrosion resulted from the neighboring galvanic cells framed between the \(\alpha\)-phase particles and the aluminium lattice. The particles present in the phase acted as cathodes herein. These acting cathodes allowed the decrease of oxygen and drove the anodic crumbling of the incorporating framework. The ECAP passed force to isolate these particles (Figure 9); therefore, the amount of the galvanic cells increased when the ECAP test was performed.
# Evaluation of Antioxidant and Anticorrosive Activities of _Ceriops_ _tagal_ Plant Extract
## 3 Results and Discussion
### Corrosion Inhibition
#### 3.3.3 UV-Visible Spectroscopy Analysis  
The anticorrosion effect of 1 M HCl with the presence and the absence of _C. tagal_ (600 ppm) inhibitor treatment on mild steel was determined and shown in Figure 4. The change in absorbance maximum clearly shows the formation of an inhibitor metal complex. The absorption spectra of the pure _C. tagal_ extract before immersion reveal maximum absorption at 320 nm (Figure 4a), corresponding to \(\pi\)-\(\pi\)* and \(\pi\)-\(\pi\)* transition for carbonyl C=O and N-H groups, respectively. The variation in the absorption maximum of treated _C. tagal_ (600 ppm) inhibitor solution (Figure 4b) displayed shifted absorption regions to 285 and 360 nm. These estimations reveal the significant change in the position of the absorption maximum after immersion of mild steel. Hence, the change in the absorption maximum position showed the formation of the complex between the 1 M HCl and the (600 ppm) _C. tagal_ inhibitor solution.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Conc. (ppm)** & **Amount of Mild Steel Corrodant (mg/I)** & \(\eta\) **(\%)** & \(\sigma\)****a [FOOTNOTE:]Footnote : \(\sigma\) is the standard deviation.[ENDFOOTNOTE] \\ \hline Blank & 45.214 & - & - \\
100 & 32.546 & 28 & 0.01 \\
200 & 28.541 & 37 & 0.03 \\
300 & 25.299 & 44 & 0.02 \\
400 & 20.548 & 55 & 0.04 \\
500 & 12.571 & 72 & 0.02 \\
600 & 08.254 & 82 & 0.02 \\ \hline \hline \end{tabular}
\end{table}
Table 3: AAS study for different concentrations of _C. tagal_ extract in 1 M HCl (303 \(\pm\) 1 K).
# Demonstration of High-Speed Optical Transmission at 2 \(\upmu\)m in Titanium Dioxide Waveguides
## 3 Validation of the Transmission of a 10 Gbit/s Signal
Therefore, for the length of propagation under consideration, the multimode nature of the waveguide does not seem to impair the transmission quality. Before concluding, we would like to emphasize here the fact that such measurements are not as straightforward as in the C-band. Indeed, the 2-um devices have not reached the same level of maturity and it is still difficult to find such devices commercially available. This experiment shows that despite the lack of optimized devices, error-free transmission is possible, confirming that this new waveband is definitely an effective alternative, especially if new solutions appear in the next few years.
## 2 Experimental Determination of FRP-Concrete Natural Bonding by the Push-Out Test
### Experimental Observations of the Push-Out Test
To summarize, the push-out test revealed that first, the natural bonding strength of the FRP-concrete interface was about 0.27 MPa, which was lower than the data given by the previous test [42]. The reason is that in the experiment in [42], the FRP profiles were encased by concrete, which can eliminate the interfacial separation. It should be noted that the shear stress caused by the natural bonding was not evenly distributed along the interface, to be specific, the bond stress was zero at the top and bottom ends of the interface [42], and reached its peak at the middle, which meant that the aforementioned strength in this paper was underestimated. Second, the failure of the natural bonding was brittle, and the load dropped dramatically when debonding occurred. Finally, using a SIP form could substantially increase the contact area, thereby leading to an increase in the interfacial shear capacity. Therefore, in the design of decks or beams, more ribs can be added to SIP forms to create more contact surface. Additionally, in the construction process, the existence of SIP forms eliminates the need for casting forms for concrete. Therefore, to further study the effect of SIP forms, two FRP-concrete hybrid beams were constructed and tested, which are introduced in the following section. It should be noted that flat SIP forms were used in the push-out test, but in the beam test, a more complicated SIP form was used where the ribs could provide more contact area with the concrete.
## 3 Results and Discussion
### Fermentation Color Spectral Dynamic Changes
#### 3.2.3 Hue Changes during Fermentation  
Hue refers to the dominant color. The final sampling dates had quite similar ranges of hue, from 80 to 88 (Figure 4). The hue results indicated that the samples were basically yellow to slightly greenish in color. Hue changes were shown in Maurivin B cider, with a hue peak of around 94; 71B cider had a hue peak of about 88; WY4766 cider had a hue peak of 87.5; and WLP775 cider had a hue peak of 84 at day 4. In general, the apple cider colors were similar, between yellow and green. In this study, subtle hue differences were detected from the highest hue in 71B-fermented ciders compared to the lowest hue in WY4766-fermented ciders towards the conclusion of fermentation.  
Colorimetry is used in the color characterization of apple beverages. The impact of pH and oxygen influenced the anthocyanin content and yellow compound formation in apple juice [48]. Whether the influence of the yeast strain is correlated with pH, oxygenation, color extraction, stability, or alternative factors, such as phenolic compounds, needs to be studied in the future [48].  
Figure 3: Evolution of C* (chroma) of ‘Wodarz’ apple cider during fermentation with five different yeast strains. C* represents chroma of apple cider. DAI = days after inoculation with yeast strain. Bars indicate the standard error of the mean for individual treatment with three replicates.