esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Antenna Configuration and Design Strategy
### Systematic Design Process
#### 2.2.2 Multi-Mode Reconfigurable Antenna  
It is clear from the multiband antenna design stages that the two stubs and their unique combination can generate an additional lower stub while maintaining the wideband  
Figure 3: Proposed multi-mode frequency-reconfigurable antenna: (**a**) top view, (**b**) side view; (**a**) stage 1, (**b**) stage 2, (**c**) stage 3, (**d**) stage 4.  
behavior of the radiator. Therefore, two PIN diodes are utilized to electrically connect and disconnect the stubs depending upon the user requirement. However, the diode can be triggered on or off simultaneously due to a physical connection, which is result of the stage-4 design. This arising problem is resolved by adding an additional capacitor at the junction of the stubs, as shown in Figure 2. The additional capacitor as well as the RLC load introduced by the addition of the diodes results in increased mismatching along with the shift in the lower frequency. Thus, optimization is performed by using a parametric analysis and the fine-tuned reconfigurable antenna offers four operational modes, as shown in Figure 4.  
Mode 1: In this mode, both diodes are in the off state, which results in the generation of wideband ranges of 3.9-7.15 GHz.  
Mode 2: In this mode, the diode D1 is switched off while keeping the D2 switch on, and a dual-band is achieved having a corresponding bandwidth of 1.78-1.84 GHz and 3.91-7.23 GHz.  
Mode 3: This mode is in contrast to mode 2 where diode D2 is off while the diode D1 is switched on. Tri-band behavior is observed with the respective frequency ranges of 2.1-2.19 GHz, 2.54-2.65 GHz, and 4.2-7.2 GHz.  
Mode 4: In this case, both diodes are switched on, which consequently results in the generation of another tri-band mode. Two additional lower resonances at 2.65 GHz and 3.65 GHz are achieved with respective bandwidths of 2.55-2.72 GHz and 3.5-3.85 GHz. Alongside that, wideband ranges from 4.99 to 7.15 GHz are achieved. Thus, the proposed antenna offers the advantage of having a compact size along with frequency reconfigurability by achieving three operational modes: the wideband mode, dual-band mode, and tri-band mode.
# A Backwards-Tracking Lagrangian-Eulerian Method for Viscoelastic Two-Fluid Flows
## 4 Results
### Die swell
Given the above discussion, a certain variance in the data is to be expected. However, the different results do follow the same general trend, including the swell ratios predicted with the proposed Lagrangian-Eulerian method. Another aspect is that of grid dependence. The simulation performed by [PERSON] and [PERSON] had a grid resolution which, by today's standards, was very coarse. They used six triangular finite elements across the half-width of the channel. Therefore, the resulting swell ratios should be treated with caution when comparing to more recent results. [PERSON] et al. used a uniform grid of \(\Delta x/h=1/10\) which is on the order of the coarse grid M1. \begin{table}
\begin{tabular}{l l l} \hline \hline
**Work** & **Method** & **Re** \\ \hline Current work & VOF, Lagrangian-Eulerian & 0.5 \\ [PERSON] \& [PERSON] [11] & Mixed FEM & 0 \\ [PERSON] et al. [14] & GENSMAC & 0.5 \\ [PERSON] et al. [22] & pseudo-VOF & 0.5 \\ [PERSON] et al. [24] (CCU) & VOF, Geometric scheme & 0 \\ [PERSON] et al. [24] (HRIC) & VOF, Algebraic scheme & 0 \\ [PERSON] et al. [24] (RheeTool) & VOF, Algebraic scheme (MULES) & 0.01 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Summary of numerical data as compared for the die swell flow. Figure 13: Snapshots of die swell simulation with \(S_{R}=2.5\), interface between the viscoelastic phase (green) and Newtonian phase (white) visualized by \(\alpha=0.5\). [PERSON] et al. reported the number of control volumes to be 4165, but did not specify the local cell sizes in detail. The number of control volumes is again comparable to grid M1 in the current work. [PERSON] et al. did conduct a grid dependence study with three different grids. Their finest cells were closer to the grids that were used in this work as compared to the other authors. Therefore, could be expected for the results reported in this work to be closest to the results of [PERSON] et al. given the similarities in grid resolution as well as the use of the VOF method. Their computed swell ratios are generally larger than the other literature results, with the exception of those from [PERSON] and [PERSON]. The same is also true for the swell ratios that were computed with the proposed method, particularly for increasing \(S_{R}\). In conclusion, while there is a spread between the data that are produced in different numerical studies, they follow the same general trend. The results that were obtained with the method proposed in this work follow the same trend and with the swell ratios comparable to the earlier published works.
###### Abstract
CAD/CAM systems were introduced alongside optical impressions using intraoral scanners (IOs) as part of a fully digital workflow [15; 16]. The use of digital impressions for short-span cases in implant-supported rehabilitations is currently well supported in the literature. Nevertheless, some reluctance remains regarding their use in total implant-supported rehabilitations, due to the lack of precision reported in several studies [9]. In fact, the accuracy of digital impressions is inversely proportional to the scanned area size, and factors such as the absence of anatomical landmarks, the presence of mucosa, the distance between implants, and the impression conditions and strategies can contribute to errors [16; 14; 17; 18; 19; 20]. In light of this challenge and aiming at improving the accuracy of digital impression methods in full-arch implant-supported prostheses, the use of photogrammetry technology has emerged as a viable alternative for capturing the spatial position of implants [21; 22; 23]. Although some studies have been conducted on this topic, the literature comparing implant scanning using photogrammetry for scanning with IOs is still scarce [24; 25]. Despite technological advances, gaps remain in the literature concerning the standardization of protocols for digital impressions, direct comparisons between different scanners, and assessment of their long-term clinical accuracy [26]. These questions highlight research opportunities to enhance the reliability and accuracy of scanners used in total implant rehabilitation. The objective of this in vitro study is to evaluate the precision of digital impressions in full-arch implant-supported fixed dental prostheses with various implant distributions, comparing commonly used IOs with different technologies (confocal technology and 3D motion technology) and photogrammetry equipment. In clinical practice, this study may provide relevant insights into the scanning methodology that offers the highest precision in full-arch implant digital impressions. The first null hypothesis (H\({}_{0}\)1) states that there are no differences in precision depending on the scanner used. The second null hypothesis (H\({}_{0}\)2) states that there are no differences in precision according to the various distributions of implants in the arch.
## 4 Proposed mmWave Assisted CR-IoV
### Comparative Analysis
#### 5.3.2 Analysis of PDR  
PDR measures the data delivery efficacy of the network. For better PDR, the data loss must be reduced.  
In Figures 10 and 11, we have compared PDR with respect to the number of vehicles and attackers, respectively. When we compared PDR with the number of vehicles, we identified that the increase in the number of vehicles assists in achieving better PDR. As stated earlier, a large number of vehicles in the network increases the probability of selecting optimal forwarding nodes, which increases PDR. Though it supports optimal forwarder selection, SVM, ML-NN and 2D-Beamforming methods have no effect on the increasing number of vehicles. Both works (SVM and ML-NN) attain 74% and 75% of PDR,  
Figure 8: Throughput with respect to the number of vehicles.  
Figure 9: Throughput with respect to the number of attackers.  
respectively. That is more than 25% of packets are lost during data transmission due to a lack of optimal forwarder selection. Although OLSR is a routing protocol, the PDR is reduced to 75% due to the absence of important parameters during routing. In 5G-VANET, routing is performed with multiple metrics such that PDR is 83%. Here, the main issue is the presence of malicious users who intentionally steal the network resource. Overall, PDR achieved by existing works is insufficient to meet the growing requirements of IoV and ITS. Thus, we have combined mmWave, CR, and IoV to achieve high-level PDR. The packet loss is reduced in three aspects as follows,  
* First, we have isolated all malicious nodes from the network.
* Secondly, we produce optimal beams based on important AF and beampattern functions.
* Finally, we have selected optimal forwarders within FZ based on multiple objective functions.  
With the above advantages, we have achieved better PDR with respect to the number of vehicles. When it comes to the number of attackers, attack detection plays a vital role. With a poor attack detection procedure, the involvement of attackers will be increased. When the number of attackers increases, then a huge amount of spectrum is used by the attacker. Thus, PDR is reduced to 60% and 66% in SVM and ML methods, respectively. In general, SVM has lower accuracy when the conventional linear or RBF kernel is used. In mmWave-assisted CR-IoV, we have improved HK-SVM with the use of a hybrid kernel function. Further, we have presented separate algorithms for SSDF and P  
Figure 11: PDR with respect to the number of attackers.  
Figure 10: PDR with respect to the number of vehicles.  
assures the network is free from harmful attacks. Thus, we have achieved PDR up to 93% even with five attackers.
# Design of a Broadband and High-Isolation CMOS Active Quasi-Circulator
###### Abstract  
Using industry standard TSMC 90 nm CMOS technology, a broadband and high-isolation active quasi-circulator MMIC was fabricated to meet the needs of future communication system integration. An active balun and phase inverter stage made of a common-source (CS) field-effect transistor (FET) comprised the quasi-circulator that was suggested. A cascade CS stage was used to produce the active balun, which increased the isolation of \(|\)S12\(|\) and \(|\)S23\(|\) through the unilateral characteristic of the FET and allowed for transmission of \(|\)S21\(|\) and \(|\)S32\(|\). Further, a CS FET connected in parallel to ports 1 and 3 for phase cancellation can effectively increase the quasi-circulator's isolation \(|\)S31\(|\). Theoretical analysis for the detailed circuit was shown in the main paper. The results show that all isolations are better than 20 dB over 5-33 GHz, and the measured findings reveal that the suggested quasi-circulator has an insertion loss of less than 10 dB. It is possible to reach an isolation level of 55 dB between ports 1 and 3, which is greater than present research.  
broadband; isolation; phase cancellation; quasi-circulator; active balun +
Footnote †: journal: Applied sciences
## 3 Analysis of Test Results  
### Stress-Strain Curve  
Uniaxial compression tests were conducted on intact, hole-containing, and cement-filled specimens by using a multifunctional rock mechanics tester to investigate the impact of cement slurry filling on the mechanical behavior of marble with holes. The outcomes of these tests on various specimens are presented in Table 1.  
The uniaxial compression tests were carried out on intact, hole-containing and cement paste-filled specimens, and the stress-strain curves were obtained as shown in Figure 2. The stress-strain curve of the intact specimens is shown in Figure 2a. The curve shows a small compressive dense phase at the beginning of loading, and with the progressive increase in pressure, the rock specimens enter the linear elastic phase, and the slope of the curve tends to stabilize. The stress-strain curve of the hole-containing specimens is shown in Figure 2b. In comparison with the intact rock specimens, the hole-containing rock specimens reach the peak value when the strain reaches about 0.2%, and the residual strength of the rock specimens falls close to 0 a while after the peak value. Figure 2c shows the stress-strain curve of the cement-filled specimens. The cement filling has an obvious improving effect on the strength of hole-containing rock, because the filling can also bear a part of the pressure, and its peak and residual strengths are improved to different degrees compared with the hole-containing rock specimens.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Number** & **Peak Strength, MPa** & **Average Peak Intensity, MPa** & **Peak Strain, \%** & **Average Peak Strain, \%** & **Average Modulus of Elasticity, GPa** & **Average Residual Strength, MPa** \\ \hline Int-1 & 131.85 & & 0.338 & & \\ Int-2 & 129.35 & 131.91 & 0.317 & 0.325 & 51.31 & 28.19 \\ Int-3 & 134.53 & & 0.321 & & \\ \hline Fla-1 & 75.39 & & 0.291 & & \\ Fla-2 & 74.69 & 73.78 & 0.273 & 0.265 & 45.04 & 20.09 \\ Fla-3 & 71.27 & & 0.232 & & \\ \hline Fill-1 & 57.64 & & 0.192 & & \\ Fill-2 & 60.29 & 60.28 & 0.199 & 0.195 & 41.89 & 2.65 \\ Fill-3 & 62.93 & & 0.194 & & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Results of tests.  
In summary, the typical intact, unfilled, and cement-filled specimens all pass through five stages, i.e., intact compression, density, linear elasticity, elastic-plastic transition, and plasticity-destruction, in the test, and their peak strengths, peak strains, and elastic moduli decrease sequentially. It is also worth noting that the post-peak residual strength of the intact and cement-filled specimens is around 20 MPa, whereas the residual strength of the hole-containing specimens is close to zero.
# A Review of Converging Technologies in eHealth Pertaining to Artificial Intelligence
## 3 Challenges of eHealth and AI Applications in Healthcare
### Security and Privacy of Health Information  
One major concern in utilizing any technology that transmits or manipulates healthcare records is the security and privacy of such information. In [57], healthcare records are protected from malicious-intent users through a combination of artificial intelligence-based agents and smart contracts generated through the use of blockchain technology, making sensitive health records distributed and immutable. The mixture of eHealth and blockchain for the purpose of protecting health data seems to provide a well-acknowledged solution, as we see in [23] and in combination with AI in [15].  
Some attempts at securing healthcare environments use encryption and the cloud, in addition to AI, for the management of the blood bank supply chain with reduced human intervention [58].
# Online Forecasting and Anomaly Detection Based on the ARIMA Model
## 2 Materials and Methods
### Performance Metric for the Forecasting Problem  
To evaluate the forecasting algorithms, the Mean Absolute Percentage Error was used (Equation (4)). The main motivation for choosing this metric is the easy interpretability of the results and the ability to compare forecast errors between different physical measures.  
\[\text{MAPE}(X_{t},\widehat{X}_{t})=\frac{1}{T}\sum_{t=1}^{T}\frac{|X_{t}- \widehat{X}_{t}|}{\max(\epsilon,|X_{t}|)} \tag{4}\]  
where \(\widehat{X}_{t}\) is a predicted value at a time moment \(t\), \(X_{t}\) is a true value at time moment t, \(T\) is the number of points in time series \(X\), and \(\epsilon\) is an arbitrarily small yet strictly positive number to avoid undefined results when \(X_{t}\) is zero--in our case, \(\epsilon=2.22\cdot 10^{-16}\).
# Sentiment Analysis of Students' Feedback on E-Learning Using a Hybrid Fuzzy Model
## 2 Preliminaries
### Deep Neural Networks
#### 2.1.3 Comparison between LSTM-Based Models and Transformers  
Both LSTMs and transformers are popular choices for sentiment analysis, but they have different architectures and characteristics [30]. The choice between an LSTM and transformers for sentiment analysis depends on factors such as the size of the dataset, computational resources, and the specific characteristics of the task. LSTMs are suitable for smaller datasets and tasks where sequential processing is crucial, as in our case where we have used a small dataset of a Saudi dialect where the words' order within the text is very important for the sentiment extraction task. For all these reasons, we have opted for an LSTM-based model. Nevertheless, transformers can be used as an extension for this work if we aim to expand our dataset.
## 3 Case Studies
### DCMG Model in MATLAB/Simulink  
The development of simulation models is essential when it comes to investigating power quality in electricity networks, as it allows different scenarios to be analyzed without affecting the operation of a real network. They help to predict problems such as voltage variations and harmonic distortion. Simulations make it easier to evaluate new technologies and solutions before they are applied in practice, and they also make it possible to test the network under extreme or rare conditions, such as faults or overloads, without compromising a real system. A DCMG model was therefore drawn up for simulation in MATLAB/Simulink software, as shown in Figure 6.  
The model has a unipolar radial topology based on a two-level hierarchical control, that consists of a PV system, a wind power system, a BESS, an interface with the AC grid, AC and DC loads.  
The model followed the voltage levels according to IEC TR 63282 [20], so the DC bus has a nominal voltage of 700 V. The nominal AC grid voltage is 230 V/50 Hz.  
\begin{table}
\begin{tabular}{c c} \hline \hline
1 HVS module & 2.56 kWh, 102.4 V \\ \hline Number of modules & 2 \\ \hline Capacity & 5.12 kWh \\ \hline Maximum output current & 25 A \\ \hline Peak output current & 50 A, 5 s \\ \hline Nominal voltage & 204 V \\ \hline Operating voltage & 160–230 V \\ \hline \hline \end{tabular}
\end{table}
Table 4: Technical features of BYD HVS 5.1.  
\begin{table}
\begin{tabular}{c c} \hline \hline \(U_{ACnom}\) & 230–400 V/220–380 V \\ \hline \(I_{ACnom}\) & 14.5 A/15.2 A \\ \hline \(f_{ACnom}\) & 50/60 Hz \\ \hline \(S_{nom}/S_{max}\) & 10,000 VA \\ \hline \(P_{max}(cos\varphi=1)\) & 10 kW \\ \hline \(U_{DC_{PP}}\)\(mpp\) & 278–800 V \\ \hline \(U_{DC_{PP}}\)\(min/max\) & 80–1000 V \\ \hline \(I_{DC_{PP}}\)\(max\) & 25.0 A/12.5 A \\ \hline \(I_{SC_{PP}}\) & 37.5 A/18.8 A \\ \hline \(U_{DC_{Mat}}\)\(min/max\) & 160–700 V \\ \hline \(I_{DC_{Mat}}\)\(max\) & 22 A \\ \hline \hline \end{tabular}
\end{table}
Table 5: Technical features of Fronius Symo GEN24 10.0 inverter.  
The DCMG control, components and systems used in the model will be discussed in more detail in the following subsections.
## 2 Related Work
The intrusion detection technique uses an intrusion detection system (IDS) to find intrusions. [PERSON] created the space-effective probabilistic data structure called the Bloom filter 1970. False eight-match positives can happen, but false negatives cannot. The result of a query is either \"possibly in the set\" or \"definitely not in the set\", in other words. The number of items added affects the likelihood of false positives; elements can be added to the set but not removed (although the counting Bloom filter variant can address this issue). In general, the Bloom filters sufferfrom generating false positives. However, the space complexity will be reduced compared to other data structures, including hash tables and linked lists, because they do not store the actual data items. Pointers add additional linear space overhead to related systems. A flexible \"service-based\" applications scheme for smart cities was developed by [PERSON] et al. [9]. They were using a large volume of multimedia data. They also have a robust \"mathematical model\" for data packet routing. The recommended approach ensures \"quality of service (QoS)\" in \"multimedia security\" and \"safety applications\" while allowing for data routing on available vehicle assets. To determine the proposed model's applicability, they conducted an \"analytical study\" to \"validate the simulation\" results regarding the \"packet received ratio\", energy usage, and \"average end-to-end delay\". An upcoming Internet of Things network design and the security issues it raises were presented by [PERSON] et al. [10]. in their article. [PERSON] et al. proposed a \"lightweight authentication solution\" for \"M2M communications in an Industrial IoT environment\" based solely on \"hash and XOR operations\". The proposed mechanism achieves \"mutual authentication\", \"session key agreement\", \"device identity confidentiality\", and \"resistance to ancillary attacks such as replay attacks\", \"man-in-the-middle attacks\", \"impersonation attacks\", and \"modification attacks\" while having a low \"computational cost\", \"communication overhead\", and \"storage overhead\". Software-defined networking denotes \"sophisticated traffic control\" and \"resource management components\" in a coherently concentrated system control plane [8]. Fog computing, in contrast, enables small amounts of data to be analyzed and monitored at the \"network edge\", supporting the applications that require \"extremely low\" and \"predictable latency\". They also assessed the benefits and potential services of the proposed design, as did [PERSON]. As a low-energy routing strategy for WSNs, \"survivable path routing\" was developed. This protocol should work in high-traffic environments, such as those used by \"IoT applications for remote healthcare monitoring\", when \"many sources\" simultaneously attempt to deliver packets to the exact location. The next hop of the node is decided by the four factors, including the \"signal-to-interference ratio\", \"noise ratio of the link\", \"survival factor of the path\", and \"congestion level at the next-hop node\".