esa-sceva/satcom-chunk-collection huggingface dataset:
# Design and Signal-Decoding Test Verification of Dual-Channel Round Inductsyn Decoding Circuit
## 3 Decoding-Circuit Hardware Design
### Design of Induced-Signal Processing Circuit
The filtering circuit is designed as a third-order Butterworth low-pass filter, as shown in the circuit schematic in Figure 5. By adjusting the potentiometer R4 at the inverting input of the lower-left operational amplifier AD8694 in the diagram, the gain of the filter can be finely adjusted within the range of 0.5-0.8. The final stage of the decoding circuit is the phase adjustment circuit. According to the previous description, the phase difference between the excitation signal and the sine-/cosine-induced signals of the AD2S1210 should be less than 44\({}^{\circ}\). Due to the fact that the round inductsyn is not a purely resistive component, and considering the presence of amplification and filtering circuits, the induced-signal output after processing is inevitably prone to phase shift compared to the excitation signal. This can significantly impact the decoding accuracy of the AD2S1210. Therefore, in the final stage of the decoding circuit, a notch filter based on LF347 has been designed. Through this stage, it is theoretically possible to achieve a phase shift of the signal between 0 and 180\({}^{\circ}\). In the schematic diagram of the induced-signal processing circuit shown in Figure 5, by adjusting the potentiometer R39 at the inverting input of the LF347, it is possible to achieve the phase shifting of the signal to the desired phase.
## 3 Experiments and Results
### Registration of the Shock Wave Impulse Using a Hydrophone  
The second method of measuring the shock wave is using a hydrophone to record the impulse of the shock wave (acoustic wave) propagating in the water tank where the transmitter was immersed. The schema of the test bench with a hydrophone is shown in Figure 8.  
In our solution, the transmitter was immersed in water. In contrast, in paper [23], a barrier in the form of a rubber membrane was used, the role of which was to propagate the generated wave on the transmitter's front into the water tank.  
As the hydrophone, we used a probe terminated with a ceramic piezoelectric element (constructed following the standard [12]). In a 5-L tank of distilled water (temp. 24 \({}^{\circ}\)C), the transmitter head of the applicator mounted vertically in a stand was immersed, as in papers [1; 7; 8; 9]. At a distance of 10 mm [22] from the face of the transmitter, we placed a probe immersed in the tank in the axis of rotation of the transmitter. At the terminals of the probe, a voltage corresponding to the recorded amplitude of the shock wave pressure was  
Figure 8: Test bench with a hydrophone and transmitter immersed in the water tank.  
Figure 7: Energy flux density (expressed as quadrature of pulse) and the operating frequency for pneumatic applicator—measured by vibrometer.  
generated. As in the case of the vibrometer test bench, this voltage was subjected to further processing, whereas the measurements were subjected to statistical analysis.  
The standard [11] recommends using water tanks large enough for experiments to avoid the phenomenon of shock wave reflection from the tank walls and the formation of a standing wave. Here, we used a different approach, i.e., we inserted an adaptive filter to process the measurement value from the probe, which allowed us to capture the original shock wave and not its reflection.  
Figure 9 shows the graph of the relationship between the applicator operating frequency and the energy of the shock wave (more precisely, the quadrature of the positive wave phase). This time, we carried out the experiments for a wider frequency range of 1-15 Hz. Again, results were obtained empirically, confirming the hypothesis also given in papers [7; 8; 9], i.e., with increasing frequency, the energy of the shock wave decreases. As reported in papers [7; 8; 24], in the 1-10 Hz range, the energy of the shock wave decreased by more than 30 percent. Based on the results from the paper [20], we can assume that there was also a decrease in the intensity of cavitation phenomena.
## 3 Binocular System  
Although holography is a true 3D display, the limitation of the holographic device, such as a big pixel pitch of SLM, leads to a small viewing angle. To increase the viewing angle, it is necessary to tile multiple SLMs. Therefore, we propose a binocular holographic HMD system using two tiled SLMs for holographic HMD. As shown in Figure 6, there are two SLMs tiled in a curved configuration with tiled angle \(\alpha\) in order to ensure accurate tiling. When \(\alpha\) is smaller than \(\theta\), the viewing angle is increased to \(\theta\)+\(\alpha\) in this case [23], otherwise, the reconstructed image is not seen continuously. Under ideal conditions, i.e., \(\alpha=\theta\), the dependence of the viewing angle on the pixel pitch of SLMs is as shown in Figure 7a. The dependence of the distance between the image and eyes on the pixel pitch of SLMs is shown in Figure 7b.  
Figure 5: (**a**) Image plane and convergence plane of the stereoscopic display. (**b**) Image plane and convergence plane of the holographic display (the convergence plane is the same as the interaction plane). HMD, head-mounted display.  
Figure 6: Viewing angle of two tiled SLMs.  
Figure 8 shows a schematic diagram of the proposed binocular holographic HMD system. The tiled SLM unit consists of two SLMs (SLM1 and SLM2 with the same pixel pitch) and a beam splitter (BS). Some of the laser beam is reflected by the BS to SLM1 and reads out one computer-generated hologram display in SLM1, and then, the reconstructed image transmits through the BS and combines with the reconstructed image from SLM2, which is reflected by the BS after it is read out from the other computer-generated hologram display in SLM2 by the laser beam, which transmits through the BS. These two holograms displayed in SLM1 and SLM2 have different viewing angles of an object or a scene.
# Study of Implantation Defects in CVD Graphene by Optical and Electrical Methods
## 3 Results
### Raman Measurements
The solid line shown in Figure 4 represents the relation of 2D versus G for graphene of concentration smaller than 1 \(\times\) 10\({}^{12}\) cm\({}^{-2}\). The drift of clouds of experimental points toward higher wave numbers of the G mode (along the dotted line) represents the increase of carrier concentration [14]. Groups of points shown in Figure 4 correspond to helium ion implantation fluences of 1 \(\times\) 10\({}^{13}\) cm\({}^{-2}\), 1 \(\times\) 10\({}^{14}\) cm\({}^{-2}\) and 5 \(\times\) 10\({}^{14}\) cm\({}^{-2}\). It can be seen that with increase of implantation fluence the \"clouds\" of points move toward the lower wave numbers of the G mode, which indicates a decrease of carrier concentration [14]. Figure 4: The Raman 2D mode versus the G mode wave numbers for 1 \(\times\) 10\({}^{13}\) cm\({}^{-2}\), 1 \(\times\) 10\({}^{14}\) cm\({}^{-2}\) and 5 \(\times\) 10\({}^{14}\) cm\({}^{-2}\) helium ion implantation fluences. The broken lines represent average of the observed ‘clouds’ of points. The solid line corresponds to slope of 2D versus G equal 2.2 resulting from pure strain [19], and the dotted line corresponds to slope 0.7 appropriate to strain free p-type graphene [19]. Figure 3: Ratio of intensities of Raman lines \(I(D)/I(G)\) versus ion fluence for graphene on 6H–SiC (0001) bombarded with nitrogen ions (squares) and helium ions (triangles). Solid line represents theoretical curve of \(I(D)/I(G)\) vs. ion fluence according to [18] for \(N_{D}=1\) and \(r_{S}=1\) nm. Dotted and dashed lines represent theoretical dependence of \(I(D)/I(G)\) for \(r_{S}=1.34\) nm and \(r_{S}=1.5\) nm and ion defect efficiencies \(N_{D}=0.045\) and 0.0025 for N\({}^{+}\) and He\({}^{+}\) respectively. Finally, the ratio of intensity of \(I(D)/I(D^{\prime})\) provides information about the nature of defects [21; 22]. This ratio was found to be constant and close to 6-7 in the region where the D' line was observed. This value indicates that the dominant graphene defects generated by ion implantation are vacancies.
### Leveraging Software-Defined Networking (SDNs) in the Design of IIoT-Edge Networks
[97] compared ODL against Floodlight using the Mininet emulator and concluded with a 95% confidence interval that ODL outperforms Floodlight in low-loaded networks and tree topologies in mid-loaded networks in terms of latency. However, they also concluded that Floodlight can outperform ODL in heavily loaded networks for tree topologies in terms of packet loss and linear topologies in terms of latency. **For the scalability benchmark:** [PERSON] et al. [102] observed that ONOS outperformed ODL, Ryu, and Floodlight and were affected by increased workloads. They also noted that SDN controller placement affects performance across various network topologies. Currently, researchers are experimenting with customized SDN controllers specific to certain applications. [PERSON] et al. [85] propose deploying customized SDN controllers that can accommodate protocol interpreters for IoT application scenarios. Drawing upon the findings of the experimental studies discussed, the choice of an SDN controller should be contingent upon specific application requirements, given the diverse advantages and disadvantages observed among the SDN controllers evaluated. This necessitates the careful consideration of trade-offs to align with the intended application environment's operational demands and performance expectations.
## 4 VRIS Multidimensional Assessment
### Security Analysis
#### 4.3.2 Experimental Results  
Security is also a vital metric in evaluating image steganography models. In this study, we enhanced the security of the image steganography algorithm by adding random noise to the first-level encrypted image, thereby increasing the difficulty for unauthorized users to extract the secret information. The presence of noise prevents unauthorized users from directly extracting the hidden secret information from the encrypted image without undergoing additional processing. The addition of noise makes the secret information more difficult to analyze and extract, effectively safeguarding the security of the hidden information. Without sufficient information and keys, unauthorized users find it challenging to restore the original secret information, thereby protecting the confidentiality of the information. The specific experimental results are presented in Table 5.  
In summary, by adding noise to the first-level encrypted image, we can confuse unauthorized users' analysis of the image content, enhancing the security of image steganography algorithms. Moreover, the misclassification rate is a crucial evaluation metric in  
Figure 6: Histogram comparison of cover image and steganographic image.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Dataset** & **Cover Image** & **Secret Image** & **Noisy Encrypted** & **Illegally Encrypted Image** & **Denoised** & **Secretly Reconstructed** \\ \hline  
image steganography models. We selected InceptionV3 and ResNet50 to detect the misclassification rates of second-level encrypted images generated by our steganography model under varying noise intensities. According to the experimental results (Table 6), for InceptionV3, the misclassification rate shows an overall increasing trend as the noise factor rises, reaching 87.18% on the LFW dataset. For ResNet50, the misclassification rate also fluctuates under different noise factors, peaking at 99.24% when the noise factor is 0.05, which is quite notable. This indicates that our proposed image steganography model can effectively deceive machine learning models, resulting in erroneous classification outcomes while concealing secret images, demonstrating significant security and robustness. This is crucial for preserving the protection and privacy of steganographic information, especially in the context of sensitive data transmission and storage.  
In addition, to further verify that the VRIS model also has significant advantages in terms of effectiveness and robustness, we conducted a comparative analysis of multiple steganographic algorithms using the excellent steganalysis algorithms SRM and XuNet. The experimental results show that the VRIS model has a significant advantage in terms of misclassification rate, which is higher than that of other algorithms under both steganalysis algorithms, which indicates that VRIS has a stronger ability to evade steganalysis detection (as shown in Table 7).
# Seismic Response Effect on Base-Isolated Rigid Structures by Mass Eccentricity in Nuclear Plants
## 2 Analysis of Seismic Response in Base-Isolated Mass-Eccentric Structures  
### Response Characteristics Due to Eccentricity  
When examining examples of research related to the seismic response characteristics of structures due to eccentricity, it has been reported that, when conducting three-dimensional structural analysis on high-rise buildings, when the center of gravity in the horizontal direction is eccentric, torsional effects occur, along with bending, leading to reduced lateral load-bearing capacity [1]. This becomes more distinct if the structure is irregular along the height, according to some studies [2; 3]. Furthermore, the seismic response impact on structures with eccentricity has been observed to increase with larger eccentricities. Although maximum displacements decrease, increased torsional behavior results in concentrated damage, leading to greater damage [4].  
In the case of base-isolated structures, the response impact due to the distance between the mass center and the stiffness center of the base isolation layer has been examined. Research indicates that, while maximum response displacement does not vary significantly, maximum response acceleration, inter-story shear forces, and forces on upper floors significantly increase with larger eccentricities [5; 6]. Excessive damage is expected in some components as a result. Therefore, it is crucial to avoid eccentricity in structural placement, and it is recommended to design the mass center and stiffness center of the building to be as close as possible within allowable limits [7; 8].
# Methacrylate Polymer Monoliths for Separation Applications
## 3 Applications of Methacrylate Polymer Monoliths in Separation Science
### Challenges for the Development of Methacrylate Monoliths  
#### 3.3.1 Poor Small Analyte Separation Efficiencies  
Methacrylate-based monoliths do have limitations that need to be addressed. These form the basis for both current and future research focus. Perhaps the most significant is that of the relatively poor separation efficiencies displayed for smaller analytes due to poor mass transfer characteristics. Much work has been done to elucidate the relationship between porosity, flow characteristics and mass transfer within the monolith [160; 161; 162; 163], particularly for the separation of smaller molecules. Tracer molecules such as uracil have often been used to study the mass transport and retention characteristics of small molecules in experiments which show the dispersion of the analyte or tracer in the column with respect to elution time [162]. In addition, for the separation of large biomolecules, most separations are performed in gradient mode, improving peak sharpness due to reduced adsorption of the biomolecule. However, the use of gradient elution means that comparisons between individual monolith samples cannot be reliably performed due to the different flow rates, solvent compositions and pressures utilized between different runs. Therefore, the ideal method for comparison purposes would involve an isocratic separation, however, this may not lead to the best separation, but one which can be reliably compared to other separations using similar monolith samples.
# Multi-Sensor Precipitation Estimation from Space: Data Sources, Methods and Validation
## 6 Validation
### Data Preprocessing and Statistical Metrics
The D value represents the disparity between the SPE and reference data.
## 2 Reviewing Background and Related Work
### Real-Time Quality Control
When using service agent tools to support IoT service quality monitoring and ensuring the convenience of packet delivery on the communication link, it is also necessary to consider whether the data can be accurately delivered to the destination. Since the current communication method of MQTT broadcast is mainly used to facilitate data transmission, communication registration is used to perform simple operations to authenticate the connection. In the broadcast packet, there is no framework for securing the link to the package message. Based on IoT communication, broadcast is a continuous and long-term information exchange, a relatively risky communication channel for managing network security [8; 21; 22]. Assuming that the packet is monitored for a long time, we can observe that when the authentication of the broker connection is tested successfully, illegal numerical results that change the signaling transmission can be sent [23]. Let us take the above example of the water valve, when the temperature reaches 25 degrees Celsius. The IoT device will start the water valve to lower the temperature of the machine. After the intrusion, the temperature value received by the broker is illegally modified. Each datum is reduced by 5 degrees when it is returned. Therefore, activating the water valve to cool down at 30 degrees will result in a severe technical bottleneck and loss when the machine temperature reaches its true temperature. Since traditional computers and smartphones can use VPN (Virtual Private Network) mode to reduce possible data theft and tampering problems during data transmission, IoT device endpoint technology does not yet have good communication channel management that can reduce the obstacles to packet signal theft. Therefore, how to effectively solve the security technology management of IoT data packet transmission is an important issue.
# Stability of Bituminous Emulsion Induced by Waste Based Bio-Surfactant
## 1 Introduction  
Bitumen is a viscoelastic material derived from the petroleum industry and for this reason its chemical composition is hugely dependent on the initial crude oil and the cracking process carried out on it. It is not miscible with water and this feature is fundamental for the production of emulsions. From a chemico-physical point of view, the emulsification process involves the dispersion of a fluid in another provided that the two are not miscible with each other. When this phenomenon occurs, one of the two fluids breaks into drops, while the other exists as a continuous medium. Generally, emulsions are of two types: water in oil or oil in water, depending on whether the dispersing part (continuous medium)is water or oil [1; 2]. Emulsions of this type are thermodynamically unstable systems; in fact, their free energy decreases over time [3]. However, it is possible to stabilize an emulsion with the use of emulsifiers [4; 5].  
The latter are surfactants, i.e., molecules with a polar (hydrophilic) head and a non-polar (lipophilic) tail. Thanks to their amphiphilic nature, surfactants are adsorbed at the interface of the two phases, arranging themselves with the polar head in the aqueous phase, and with the non-polar tail in the organic phase. This mechanism facilitates the reduction of the interfacial tension between the droplets and the dispersing phase [6]. Bituminous emulsion is a worldwide technology, and its first application was patented in the early 1900s [7] being mainly used for pavement maintenance and road repair. Bituminous emulsions are oil-in-water emulsions in which droplets of bitumen are dispersed in the continuous aqueous phase. In order to reduce the interfacial tension and prevent coalescence phenomena, ionic surfactants are used. The salt form of the fine surfactant is solubilized in water before its addition to the bitumen. The two fluids are poured simultaneously into a colloidal mill, whose rotation speed is between 1000 and 6000 rpm. This speed causes the breaking of the bitumen into small droplets, typically between 1 and 10 \(\upmu\)m in diameter, readily covered by the emulsifier [8; 9; 10]. The main uses of bitumen emulsions are in road building, roofing and waterproofing [11; 12; 13; 14].  
Bituminous emulsions are commonly studied in terms of stability, asphalt performance, breaking times [15; 16; 17]. Emulsions can be identified according to their chemical nature, basicity or acidity.  
The innovative endpoint of the research work behind this article is to make bitumens emulsifiable or rather to understand why some bitumens are not emulsifiable. In this work, only basic emulsions are investigated, without compromising the generality of the proposed methodological approach. Not all types of bitumen used in the road paving sector are emulsifiable under basic conditions. This work therefore aims to identify the chemico-physical causes of the non-emulsifiability of the aforementioned bitumens and to find suitable additives capable of making them emulsifiable [14].
# Electroencephalography (EEG) Technology Applications and Available Devices
#### 2.1.3 Wet EEG Devices  
There are different types of wet EEG devices discussed below (Figure 1).  
**Soft gel-based:** Using this connection, electrodes connect with the scalp by applying conductive gel into the pocket of each electrode. After completion of an experiment, it is necessary to clean the headset by removing the gel and cleaning the electrodes. This is often done with alcohol because of its evaporative properties [3,4].  
**Saline solution:** Some of the EEG headsets require a conductive gel to help make low-impedance electrical contact between the skin and the sensor electrode. EEG headsets that have this technology connect electrodes by applying saline to each electrode [3,4].  
**Dry:** Dry EEG devices do not use any gel or saline to connect the electrodes with the scalp, which makes it easier to record EEG data without the help of a trained technician [3,4]. Furthermore, its setup time is considerably shorter than wet headsets.  
**Others:** Some EEG sensor connections types do not fit cleanly into either of these two categories. Conductive solid gel materials, such as those produced by Enobio, have also been used successfully in EEG devices.