esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Numerical Results
### The Implementation of the Suggested Method on an 80-Unit System  
In order to demonstrate the efficiency of the suggested method, a larger system with 80 thermal generating units with multi-fuel options and vale point loading effects was considered [11]. The load demand of the system was 21,600 MW. The study case was an expanded case of the 10-unit system with MFs and VPEs in Section 5.1.2 above. Compared methods had the same challenge of a discontinuous objective function and a high number of control variables. The comparisons with CSA, RCSA, and ALO are shown in Table 5. Because it is a complicated study case, the improvement of the proposed method over its conventional method can be seen clearly. The _ic_ over ALO was 0.194%, but  
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Method**} & **Best Cost** & **Mean Cost** & **Worst Cost** & \multirow{2}{*}{\(S_{\textit{td}}\)} & \multirow{2}{*}{_CPU (s)_} & \multirow{2}{*}{\(N_{\textit{p}}\)} & \multirow{2}{*}{\(G_{\textit{max}}\)} & \multirow{2}{*}{\(N_{\textit{fes}}\)} & \multirow{2}{*}{_ic (\%)_} \\  & **(S/h)** & **(S/h)** & & & & & & & \\ \hline IA [39] & 62,466.8044 & 62,528.9870 & 62,487.5109 & 12.038 & 1.93 & 5 & - & 20,000 & 0.016 \\ RCSA [29] & 62,456.6331 & 62,456.6331 & 62,456.6332 & 0 & 0.31 & 10 & 500 & 10,000 & 0.000 \\ CBOA [41] & 62,456.6328 & - & - & - & - & 40 & 300 & 12,000 & 0.000 \\ SHO [45] & 62,456.6331 & - & - & - & - & 100 & 1000 & 100,000 & 0.000 \\ ALO & 62,456.6647 & 62,457.8345 & 62,461.8382 & 1.1432 & 7.40 & 30 & 300 & 9000 & 0.000 \\ IALO & 62,456.6331 & 62,456.6341 & 62,456.6442 & 0.0019 & 0.30 & 30 & 150 & 4500 & \\ \hline \hline \end{tabular}
\end{table}
Table 4: The comparison of results for a 20-unit system.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multicolumn{1}{c}{**Method**} & **Best Cost (S/h)** & **Mean Cost (\$/h)** & **Worst Cost (S/h)** & \(N_{\textit{fs}}\) & _ic (\%)_ \\ \hline RCGA [12] & 624.6605 & 625.9201 & 628.9253 & 3000 & 0.0481 \\ NRCGA [12] & 624.3550 & 624.5792 & 624.7541 & 3000 & \(-0.001\) \\ FOA [37] & 673.5544 & 685.2872 & 699.2855 & 6000 & 7.304 \\ IFOA [37] & 624.4951 & 625.2647 & 629.3951 & 3000 & 0.022 \\ ALO & 624.3891 & 624.3894 & 624.3894 & 3000 & 0.005 \\ IALO & 624.3735 & 626.0487 & 630.5104 & 3000 & \\ \hline \hline \end{tabular}
\end{table}
Table 3: The comparison of results for case 3 of the 10-unit system.  
this value is much smaller compared to those of CSA and RCSA, where the values of _ic_ were only 0.01% and 0.005, respectively. The insignificant improvement can be understood because the two methods were run by using 132,000 fitness evaluations while the proposed method was run by using only 80,000 evaluations. For this case, the proposed method was the fastest method and reached the best solution. So, it is a very efficient method for a large-scale, 80-unit system considering MFs and VPEs.
# Optimal Model-Free Mean-Square Consensus for Multi-Agents with Markov Switching Topology
## 5 Simulation Examples  
Figure 2 illustrates the MASs comprising one leader and six followers. The applicability of the established technique with Markovian switching topologies will be demonstrated by this example. For the Markovian process \(\sigma(k)\), we select the transition probability matrix as  
\[P=\begin{bmatrix}0.2&0.8\\ 0.3&0.7\end{bmatrix},\]  
whose states are shown in Figure 3. As can be observed, \(\mathcal{G}_{un}\) contains a directed spanning tree. The topology alternates at random between \(\mathcal{G}_{1}\) and \(\mathcal{G}_{2}\).  
Figure 1: Learning process of actor–critic NNs.  
We consider system dynamics with  
\[A=\begin{bmatrix}0.995&-0.09983\\ 0.09983&0.995\end{bmatrix},\]  
\[B_{1}=\begin{bmatrix}1\\ 1\end{bmatrix},\ B_{2}=\begin{bmatrix}1\\ 0.9\end{bmatrix},\ B_{3}=\begin{bmatrix}0.6\\ 0.8\end{bmatrix},\ B_{4}=\begin{bmatrix}0.5\\ 0.5\end{bmatrix},\ B_{5}=\begin{bmatrix}0.8\\ 0.9\end{bmatrix},\ B_{6}=\begin{bmatrix}0.9\\ 0.8\end{bmatrix},\]  
and the leader dynamic is \(x_{0}(k+1)=Ax_{0}(k)\). We choose \(Q_{ii}=I_{2}>0\), which means giving equal weight to the errors of all state variables, because we want the errors of all state variables to be minimized evenly, resulting in better tracking and synchronization performance. Choosing \(R_{ii}=R_{21}=R_{43}=R_{54}=R_{65}=1\) and the others \(R_{ij}=0\) for \(\forall i,j=1,2,\dots,6,\ i\
eq j\) means that the control input cost is the same for each agent. This setting can avoid the control input being too large so as to ensure the smooth control signal and system stability. Our activation functions were adjusted to resemble those of [31]. Setting the discount factor as \(\gamma=0.95\) assigns a high weight to future rewards while not completely ignoring immediate rewards. This setting helps the algorithm to find a balance between long-term and short-term performance, thereby achieving better control outcomes. And, setting the learning rates as \(\beta_{c}=\beta_{a}=0.05\) gives a good balance between stability and speed of convergence.  
As demonstrated by Figure 4, the system state trajectories of all agents show that, even if the followers begin at various initial states, after a few iterations, they all converge to consensus with the leader. Figure 5, which depicts the LNTE of the MASs, demonstrates how all follower tracking errors tend toward zero. Figure 6 displays the state dynamics of the MASs in a three-dimensional phase space. The results indicate that the states of the followers and the leader ultimately converge to be identical. The findings from the simulation show that the method that we recommend can effectively address the consensus problem.  
Figure 3: Markovian switching signal.  
Figure 4: State trajectories of the leader and follower agents.  
Figure 5: Tracking errors.  
Figure 6: Three-dimensional phase plane plot.
## 3 Results and Discussion
### GPC Measurements  
To gain some insight on the molecular weight distribution of the PEAs synthesized, all polymers were subjected to GPC measurements. The molecular weights of the PEAs are obtained in a gaussian distribution, which is expected for polycondensation reactions. In addition, the PEAs synthesized possess molecular weights of around 300 to 12,000 g/mol, which is reasonable for UV-curing resins. However, as the calibration of the measurements had a cutoff of 575 g/mol, M\({}_{\text{n}}\), M\({}_{\text{w}}\), and D were not calculated, and only the elugram is showed in Figure 3. Furthermore, one of the major challenges associated with the synthesis of resins for UV-curing applications is the undesired premature crosslinking of the reactive double bonds during the polycondensation reaction. This leads to an increase in the molecular weight of the resins and eventually to the gelation of the resins. If such an undesired side reaction would occur, this could be detected by means of GPC analysis trough the appearance of a signal at higher molecular weight, as well as a deviation from the gaussian distribution. In all our cases, no high molecular fraction was observed, indicating that no crosslinking occurred. In addition, all of the PEAs synthesized have similar molecular weight, with slight differences for the second series, where the PEAs with the highest amide content have a slightly higher retention volume and, therefore, lower molecular weight.
# Stability-Aware Geographic Routing in Energy Harvesting Wireless Sensor Networks
## 1 Introduction
Specifically, ORPL is based on Expected Duty Cycles (EDC), a multipath equivalent of Expected Transmissions Count (ETX) [16]. The ETX metric measures link quality by calculating the expected transmissions of a packet necessary for it to be received successfully. Thus, it is considered as a passive link quality measurement because an observation time is needed. However, our proposed SAGREH can be considered as an active link quality measurement because it estimates the link quality (_i.e._, Packet Reception Rate, PRR) from the information of the distance between two nodes by using Equation (11). Moreover, our proposed SAGREH routing protocol accumulates link quality to calculate the quality in terms of PRR of all available paths from source node to sink node. Then, it selects the most reliable path for data delivery. This investigation showed that the proposed routing method outperforms the comparative routing method in terms of packet delivery ratio, average hop count, and average energy consumption when network parameters such as radio transmission range and number of nodes vary. The paper is organized as follows. In Section 2, the motivation for this research and related work is discussed. Section 3 introduces the system model, while Section 4 describes energy-harvesting-aware routing and the proposed method. Simulation results are shown in Section 5, and finally, the paper is concluded in Section 6.
# A Single-Rate Multicast Congestion Control (SRMCC) Mechanism in Information-Centric Networking
###### Abstract  
Information-centric networking (ICN) is expected to be a candidate for future internet architecture, and it supports features such as multicast that improves bandwidth utilization and transmission efficiency. However, multicast itself does not provide congestion control. When multiple multicast groups coexist, multicast traffic may exhaust all network resources, and cause network congestion and packet loss. Additionally, traditional IP multicast congestion control mechanisms cannot be directly applied to ICN architecture. Therefore, it is necessary to consider an effective congestion control mechanism for ICN multicast. This paper proposes a single-rate multicast congestion control mechanism, called SRMCC. It supports router-assisted awareness of the network congestion state and congestion control message aggregation. Moreover, the fair shared rate estimation method is innovatively proposed to achieve protocol fairness. Most importantly, it adjusts the rate according to different congestion states indicated by the queue occupancy ratio. By introducing a rate selection factor, it can achieve a balance between packet loss rate and throughput. Experimental results show that our proposal outperforms other mechanisms in throughput, packet loss rate, total bandwidth utilization, and overhead, and achieves protocol fairness and better TCP friendliness.  
m +
Footnote †: journal:  
ulticast congestion control; single-rate; queue occupancy; ICN
## 3 Results
### GC-O
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline  & & & \multicolumn{4}{c}{**Age (Months)**} & \\ \hline  & & **3** & **6** & **9** & **12** & **28** & **Approximate** & \\
**LRI** & **Compound** & & & **Frequency of Detection** & & & **Threshold** & **Descriptor** \\ \hline
506 & Dimethyl sulfide & ND & ND & ND & 2 & 1 & 0.01–0.15 & sulfur, rotten \\
593 & Diacetyl & ND & ND & 1 & 1 & 2 & 0.008–0.6 & buttery \\
587 & Ethyl acetate & ND & ND & 2 & 2 & 1 & 0.5–50 & fruity \\
658 & Propanoic acid & 3 & 4 & ND & 2 & 1 & 100–150 & rancid \\
727 & 2-methyl-1-butanol & ND & 2 & ND & 4 & 2 & 50–65 & burnt \\
745 & Isoamyl alcohol & 4 & ND & 2 & 2 & 2 & 40–70 & malt \\
790 & Ethyl butyrate & 1 & 2 & ND & 2 & 2 & 0.05–0.3 & apple \\
833 & Furfurral (2-furanal) & ND & ND & 3 & 2 & 2 & 15–25 & bread \\
875 & Isovaleric acid & 2 & 2 & 1 & 2 & 2 & 0.3–2.0 & rancid \\
880 & Hexanol & 1 & ND & 1 & ND & 1 & 4 & green \\
902 & Heptanal & ND & 2 & ND & 1 & 2 & 0.07–0.08 & rancid \\
946 & Ethyl isohexanoate & 5 & ND & ND & 3 & 2 & ND & fruit \\
1010 & Ethyl lactate & ND & ND & 1 & ND & 2 & 25 & fruit \\
1019 & Hexanoic acid & 2 & 1 & 3 & 3 & 1 & 8–10.7 & sweaty \\
1065 & Octanol & 2 & 2 & 1 & 1 & 1 & 0.9 & chemical \\
1098 & Ethyl heptanoate & ND & 2 & ND & 2 & 2 & 0.7 & fruit \\
1166 & Ethyl benzoate & ND & 2 & ND & 1 & 2 & ND & fruity \\
1168 & 4-Ethylphenol & ND & ND & 3 & 2 & 3 & 0.3 & musky \\
1204 & Decanal & ND & ND & 4 & ND & 1 & 0.006 & orange peel \\
1241 & Ethyl phenacetate & ND & ND & ND & 1 & 1 & ND & fruit \\
1253 & \(\beta\)-Phenethyl acetate & ND & ND & ND & ND & 1 & 2.5 & rose, sweet \\ \hline \hline \end{tabular} N = 6, * based upon literature values ASBC Beer Flavor Database, ND: no data, Frequency of detection.  
\end{table} 
Table 1: Aroma compounds identified in aging lambic beer using gas chromatography–olfactometry (GC–O).
# The NIRS Brain AnalyzIR Toolbox
## 3 Statistical Modules
### First-Level Statistical Models  
In many fNIRS experimental studies, the fNIRS signals between each source-to-detector pair are analyzed using a general linear regression model to test for statistical differences between the baselineand task conditions for each scan. This approach is similar to functional MRI, although several differences in the structure of noise in fNIRS compared to other modalities should be noted (see [15] for review).  
In general, first level statistical models for examining evoked signal changes are given by a regression model described by the equation  
\[Y=\mathbf{X}\times\beta+\epsilon \tag{8}\]  
where \(\mathbf{X}\) is the design matrix encoding the timing of stimulus events, \(\beta\) is the coefficient (weight) of that stimulus condition for that source-detector channel, and \(Y\) is the vector of measurements. The design matrix (\(\mathbf{X}\)) can come from either a canonical model of the expected response or a deconvolution model (see Section 3.2).
# Measurement and Analysis on Magnetic Field Influence of Substation for Magnetic Shielding Device
###### Abstract  
The residual magnetic field in a magnetic shielding device with a multilayer high permeability material (permalloy) structure can be obtained at the nanotesla (nT) level or even lower. At present, in the process of designing a magnetic shielding device, most of the external environmental magnetic field settings are set at the size of the Earth's environmental magnetic field, but the instruments inside the magnetic shielding device need to be powered, the active compensation coil needs to be powered, and the degaussing coil of passive shielding layer needs to be powered, so substations need to be used around magnetic shielding devices. The magnetic field generated by the substation will affect the magnetic shielding device, so this paper analyzes and measures the magnetic field generated by the substation. Firstly, the finite element model of a substation is established, and the influence of different substations on the environmental magnetic field is analyzed by changing the power. Secondly, the test method of a substation environment magnetic field is determined. Finally, the site test was carried out to measure the influence of different power substations and different distances on the magnetic field, and its influence on the magnetic shielding device was analyzed, which provided an important basis for the construction of the magnetic shielding device.  
magnetic shielding device; extremely weak magnetic field; substation +
Footnote †: journal: Applied Sciences
## 7 Discussion  
Relevant facts related to the COVID-19 pandemic obliges us to think about new approaches of fast application regarding the protection and monitoring of the elderly, while promoting physical distancing and keeping them in their comfort zone, with the current proposal serving as a catalyst for a fast implementation of systems that can save human lives. In the case of housing, actuators may be  
Figure 14: Distance calculation process for RSSI tests.  
Figure 13: (**a**) Boxplot graph for pRSSI; (**b**) Linear regression scatter plot graph with trend line.  
incorporated that will trigger certain actions, such as cutting the gas, water supply or electrical power, as well as triggering the discharge of fire-retardant chemicals.  
Using the system proposed, isolated inhabitants, mostly the elderly, can move freely through the outside spaces of their homes without feeling confined in terms of their freedom and privacy, and in case of suffering some type of accident, fall or change in vital signs, a distress mechanism can be triggered by entities, family or friends, acquiring access to the GPS coordinates of their most recent location.  
Taking into account both the current situation of the COVID-19 pandemic in Portugal and across the world, elderly people, who are naturally more vulnerable, and their families can benefit from this system, essentially due to the fact that family members, firefighters and security forces will have access to users' information and will be able to trigger a support action whenever any critical value in a given sensor is reached.  
By including monitoring alongside georeferencing, the event of a fall or immobilization outside the residence will also enable the triggering of rescue means.  
One of the most frequent causes of death in Portuguese rural regions has to do with carbon monoxide poisoning related to the use of braziers. This is another situation in which there can be a considerable benefit--whenever the sensors detect too high values of carbon monoxide, support teams, security forces or family members can provide support immediately.  
It is also important to refer to the data obtained in the RSSI power readings, which raise some doubts in terms of coverage, as analyzed in the results section. The global solution to solving these coverage failures must use gateways with redundant and multichannel coverage, so that there is no blocking of devices when a gateway is sending data. When a device (LoRa node) sends data, it can be received by several gateways, though, depending on the quality of the received RSSI signal, only one gateway sends data, with the other data being discarded.  
Another issue to be considered in this field is related to the placement of the antenna of each gateway, ensuring that they are properly located, at strategic points, in order to maximize the gain.
## 3 Evaluation of Building Attenuation Model
### Realistic VANET Channel Modeling  
From the models surveyed in the last section, we chose the empirical and inexpensive model of radio shadowing [5] as a realistic model that we use as a reference to compare the other two techniques, since this model is one of the most used for research in VANETs because of the following factors.  
* It relies on real measurements taken with IEEE 802.11p devices.
* It is based on a simple modification of the free-space model, which captures the building attenuation with two easy-to-compute parameters.
* Its implementation in a simulator is straightforward, and it is preloaded in VEINS, one of the most used VANET simulators.  
As we showed in [10], any realistic propagation model can be used as a reference to compare other proposals, keeping the comparison results invariable. The reason is that specific propagation models designed for VANETs provide very close results with intermediate channel capacities.
# A Single-Bit Incremental Second-Order Delta-Sigma Modulator with Coarse-Fine Input Buffer
## 1 Introduction
The proposed scheme integrates the buffer and DSM to achieve stable performance without an external buffer. The circuit designed in this research can be applied to precise measurement requiring low-noise analog signal processing without a separate external buffer. Figure 1: Conventional and proposed input buffer scheme: (**a**) Conventional external input buffer with internal pre-charge buffer; (**b**) Proposed internal coarse-fine dual input buffer.
## 3 Results and Discussion
### Wear Analysis  
Dry-sliding wear analysis is a method used to assess the wear behavior of materials under conditions of sliding contact without any lubrication. In Figure 16, the dry-sliding wear behavior of the fabricated composites is evaluated at different sliding distances (300 m, 600 m, and 900 m) using a constant sliding speed of 2 m/s and a constant applied load of 50 N. This test aims to analyze how the sliding distance affects the wear properties of the composites. The graph illustrates that the wear loss increases as the sliding distance increases. This can be attributed to the increased rubbing between the surfaces over a longer sliding distance, resulting in more material removal and higher wear loss. In other words, the more the surfaces rub against each other, the greater the wear loss experienced by the material. Additionally, the wear loss is observed to decrease with a higher concentration of reinforcement in the composites. This reduction in wear loss is due to the presence of the reinforcement particles between the pin material (sample) and the disc. These reinforcement particles act as solid lubricants when they are removed from the pin material during the initial stages of wear. This solid lubrication effect reduces the friction and wear between the surfaces, resulting in a lower wear loss. However, as the sliding distance increases, the wear loss also increases. This is because the longer duration of rubbing between the surfaces leads to more material removal and wear, outweighing the beneficial effect of the solid lubrication provided by the reinforcement particles. Comparing these findings to past research, it is observed that the addition of graphite to the composites results in a decrease in wear resistance. Graphite tends to have a lower wear resistance compared to  
Figure 15: Influence of Si\({}_{3}\)N\({}_{4}\) on forgeability of AZ91/x-Si\({}_{3}\)N\({}_{4}\) composites at a different load.  
other reinforcement materials. Therefore, the inclusion of graphite in the composites can lead to increased wear loss [39].