esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Discussion  
Nowadays, DL methods have gained considerable traction in seismic applications. CNNs are particularly popular for seismic inversion. However, using only the convolutional layer in the network to learn the complex mapping relationship between seismic data and elastic parameters leads to a lack of temporal information in the inversion results. Furthermore, traditional 1D trace-by-trace inversion methods lack spatial information and lateral continuity. To address these issues, the proposed method, M2S-MFCRGRU, combines the GRU component and M2S strategy to capture both temporal and spatial information. The experiments in Section 3 demonstrate the superior inversion performance of M2S-MFCRGRU. In more detail, the inversion results exhibit superior horizontal continuity, vertical resolution, and alignment with logging data. Furthermore, despite a longer training time compared to the other three methods, the proposed method demonstrates better noise resistance and generalization capability.  
While the proposed method M2S-MFCRGRU achieves impressive inversion performance, there are several aspects that can be further explored and improved upon. Firstly, besides adding the GRU component to the network, other components could be incorporated to extract features of different scales. For example, the transformer module can extract global features, overcoming the limitations of receptive field sizes in CNNs. Therefore, different components can be explored to enhance inversion performance. Secondly, M2S-MFCRGRU is a supervised method that relies on high-quality and large-quantity label data. Due to limitations in label data, exploring semi-supervised or unsupervised methods for seismic inversion will be beneficial. In this regard, leveraging physical constraints for seismic inversion warrants further investigation. Thirdly, although the M2S strategy shows advantages over the traditional 1D trace-by-trace method, it does not represent the typical 2D inversion approach. To tackle the 2D inversion problem, exploring a multi-trace to multi-trace strategy could be fruitful. Lastly, pre-stack seismic inversion can generate more comprehensive elastic parameters, aiding in distinguishing between lithology and oil-gas possibilities during fieldwork and providing a richer and more accurate basis for drilling. However, this work focuses on inverting post-stack seismic data. Consequently, improving the network topology to invert pre-stack seismic data will be a future goal.
# An Optimized Planning Tool for Microwave Terrestrial and Satellite Link Design
## 3 Tool Description
### Satellite Links
#### 3.5.2 Orbit Selection  
In this step, a set of preconfigured orbits is offered to the user in order to define the satellite orbit that the communication system will use as its base. The information about the current active satellites provided by CelesTrak at [[http://celestrak.org/NORAD/elements/active.txt](http://celestrak.org/NORAD/elements/active.txt)]([http://celestrak.org/NORAD/elements/active.txt](http://celestrak.org/NORAD/elements/active.txt)) (accessed on 27 December 2022) is fetched using the JavaScript fetch API and used to create these orbits. Over 3000 satellite orbit TLE coordinates are provided in this text file, which can be individually displayed in the Cesium window, upon user selection. As the user selects one of the provided orbits, the satellite entity is displayed in the Cesium window, allowing the user to see the possible satellite positions with the evolution of time. Additionally, the user can visualize the complete selected orbit by pressing the provided button, as displayed in Figure 9.  
Figure 8: Critical margin window (2).  
Figure 9: Satellite orbit elements in Cesium window.  
In Figure 9, two direct lines are also shown, which connect the antenna positions defined in the previous subsection. These direct lines are used as visual queues to indicate if the link has an uninterrupted LoS between the uplink and downlink endpoints; the red color indicates that the LoS is interrupted, and the green indicates otherwise.  
This verification was performed using the general formula of intersection between a sphere and a vector. In this case, the vector is composed between the mentioned link endpoints and the satellite position, and the sphere is representative of Earth. The intersections found can result in the following three cases:  
* Only one intersection is found, resulting in no signal blockage (case a);
* Two intersections are found, and the antenna position consists of a further intersection, having signal blockage (case b);
* Two intersections are found, and the antenna position consists of the closest intersection, having no signal blockage (case c).  
The three cases are depicted in Figure 10.
## 4 Analysis of Energy Consumption
Calculation of total power consumption (shown in Table 3) is as follows:  
* **Fat-tree: 2880 active switches, 138,240 active ports each consuming 1 W power at 1 Gbps, \(d=1\):** Power consumed \(=6.67*2880+\sum_{1}^{1}1*138,240=194,976+138,240=157.45\) kW
* **ElasticTree: 1201 active switches, 30,048 active ports each consuming 1 W power at 1 Gbps, \(d=1\):** Power consumed \(=6.67*1201+\sum_{1}^{1}1*30,048=81,307.7+30,048=38.06\) kW
* **Adaptive TrimTree: 1201 active switches, (30,048 \(-\) 7512 = 22,536) active ports each consuming 1 W power at 1 Gbps, and 7512 ports each consuming 0.3 W power at 10 Mbps, \(d=2\):** Power consumed \(=6.67*1201+\sum_{1}^{1}1*22,536+\sum_{1}^{1}0.3*7512=81,307.7+22,536+2253.6=32.8\) kW  
In power consumption computation for Adaptive TrimTree, we have assumed that none of the passive components are \"on\". As passive switches will turn \"on\", power consumption in Adaptive TrimTree will increase but that is the worst case scenario and power consumption will still be lower than both fat-tree and ElasticTree due to some links operating at reduced data rates. We varied the number of pods as 4, 8, 16, 24 and 48 and computed power consumption in fat-tree, ElasticTree and Adaptive TrimTree. The results are plotted in Figure 4 which shows a drastic increase in power consumption as the number of pods increases in the fat-tree topology but ElasticTree is quite promising and Adaptive TrimTree gives best results. Figure 4: Power consumption comparison in Fat-tree, ElasticTree and Adaptive TrimTree. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Topology**} & **Number of** & \begin{tabular}{c} **Total Number** \\ **of Active** \\ **Switches** \\ \end{tabular} & \begin{tabular}{c} **Total Number** \\ **of Servers** \\ \end{tabular} & \begin{tabular}{c} **Total Number** \\ **of Active** \\ **Ports** \\ \end{tabular} & \
\begin{tabular}{c} **Total Number** \\ **of Sports at 100** \\ **Mbps (25\%)** \\ \end{tabular} &
\begin{tabular}{c} **Total Power** \\ **Consumed** \\ **(kW)** \\ \end{tabular} \\ \hline Fat-tree & 48 & 2880 & 27,648 & 138,240 & & 157.45 \\ ElasticTree & 48 & 1201 & 27,648 & 30,048 & & 38.06 \\ Adaptive TrimTree & 48 & 1201 & 27,648 & 30,048 & 7512 & 32.8 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Power consumption in Fat-Tree, ElasticTree (MST) and Adaptive TrimTree. The power saving percentage can be calculated by using the formula given in Equation (2):  
\[ \begin{split}\text{\emph{Power saving percentage}}&=100- \text{\emph{\%Original network power}}\\ \text{\text{\% \emph{Original network power}}}&=\frac{\text{\emph{Power consumed by energy aware network}}}{\text{\emph{Power consumed by Fat--tree}}}\times 100\end{split}  \tag{2}\]  
Power saving comparison of Adaptive TrimTree (some links operating at 1 Gbps and others operating at 100 Mbps) with ElasticTree and fat-tree topology is given in Table 4.
# Decision Problem on Imperfect Inspections Combined under Two-Stage Inspection Policy
## 2 Literature Review
The two-stage inspection policy is also analysed in [23]. [PERSON] et al. assume there that a degradation signal of a system in consideration is continuously monitored by an imperfect testing method, which makes up the first stage of inspection. If a measured signal value exceeds a threshold level, perfect manual inspections start to be executed in the system. The authors' goal is to optimize inspection intervals and the threshold level with respect to the cost of the inspection and maintenance process. Similar assumptions are taken in [20]. In the result, the authors conclude that the two-stage policy with imperfect inspection of the first level 'always leads to the minimum long-run maintenance cost rate' [20] (p. 311). The literature findings prove that the two-stage inspection policy with an imperfect first stage of an inspection can be costly but fruitful when there is more than one testing method available. However, none of models assume that the second stage of the two-stage inspection policy can also be imperfect, but such a solution may be even more economical than the policies presented above. This gap was the basis to define assumptions and the goal of the developed mathematical model of the policy which considers the possibility of applying an imperfect method as the second stage of an inspection. In addition to the first shortage, there is still insufficient number of results that examine the effect of applying various periodic, imperfect inspections under a common maintenance policy and support decision process in such cases. Even the models presented above, apart from [7; 15], do not define any optimization rules or algorithms that could facilitate decision-making on the best inspection methods combination. The shortage of the results that could be supportive when deciding whether it is better to use perfect inspections (if they are available) or to combine a few imperfect methods under a common policy is fulfilled by the conclusions drawn from this research. The rules defined in the paper may be used when one searches the economic parameters of the two-stage inspection policy in a system, where imperfect inspections can (or must) be used.
# Preparation and Modification of Biochar Materials and their Application in Soil Remediation
## 3 Removal Mechanism of Major Pollutants by Biochar
### Electrostatic Interaction  
Electrostatic interaction refers to the electrostatic adsorption between the surface charge of biochar and heavy metal ions. When the pH value of solution is greater than the charge point of biochar (pH\({}_{\text{pzc}}\)), the negative charge on the surface of biochar and the heavy metal with positive charge causes electrostatic adsorption. Heavy metal ions with positive charge on the surface of biochar combine with oxygen-containing functional groups such as carboxyl, carbonyl, and hydroxyl [87; 88; 89; 90; 91].
## 3 Demonstration of Tunable Shielding Effectiveness in GHz Bands
### Dynamic Control of Shielding Effectiveness  
#### 3.2.1 Measurement Method  
According to the previous part of this paper, applying voltage to both sides of the GIG structure will achieve the tuning of the Fermi level of graphene, and the transmission performance of electromagnetic wave changes accordingly. Therefore, when the bias voltage is a modulated signal with a certain waveform, the SE of GIG structure will also exhibit certain modulation characteristics in the time domain and realize the dynamic control of SE, as shown in Figure 8a.  
Figure 8: (**a**) The diagram and (**b**) the setup of the dynamic control on SE.  
Figure 7: (**a**) The experimental photo of multilayer MIM structure; (**b**) shielding effectiveness of multilayer MIM structure with different voltages.  
Figure 8b shows the setup of the modulation performance testing process of the structure by using the waveguide method. The sample is placed between the waveguides, and arbitrary signal generated by the function signal generator is applied to the electrodes. Meanwhile, the vector network analyzer is set to the point frequency scanning mode to record the transmission coefficient at 7 GHz in the time domain, which will exhibit certain similarities with the bias signal waveform.  
Applying rectangular and triangle waves to electrodes, the transmission coefficient curves in the time domain of the MIM and BIB structure were then recorded respectively, as shown in Figure 9. Considering the symmetry of the structure, only the voltage above zero was tested.  
It can be observed that when the period of bias signal was in the second order, the sample could effectively tune the transmitted electromagnetic wave (amplitude change \(\geq\) 3 dB). When the voltage amplitude increased, the transmission coefficient decreased, indicating that the shielding efficiency of the sample increased, and vice versa. With the increase of voltage frequency, the regulation range decreased gradually, and the sample with monolayer graphene exhibited greater attenuation.  
Besides, when the voltage was switched between high and low levels, the transmission performance of the samples did not change transiently, contrarily, it changed relatively slowly, similar to the charging and discharging process of the capacitor. The main reason is that the mass and volume of anions and cations in an ion gel are much larger than those of the carriers in the graphene, and they move more slowly under the action of the electric field, which limits the regulation speed of the samples. Consistent to the case of rectangular wave bias, when the triangular wave was applied, the transmission curves of the two samples in the time domain showed a similar shape to the bias signal, where the nonlinear also mainly came from the slower moving speed of ions.  
The experimental results show the different regulation ranges and speeds of the two samples with different layers of graphene, mainly due to their different carrier concentrations.
## 7 Simulation Results  
### The Antenna Model  
In order to verify the effectiveness of the proposed method, the arbitrary baseline algorithm based on the 2D array is compared with that based on 3D array in this section. Also, the arbitrary baseline algorithm is compared with MUSIC. The simulation results and analysis are elaborated as follows.  
A twelve uniform circular array (UCA) is shown in Figure 10a. In each quadrant, four LPDA conformal antennas mounted on the cylindrical carrier are shown in Figure 10b. The approximate phase centers of arranged LPDAs are not in the same plane. The effects of mutual coupling and polarization mismatch are ignored. It can be seen in Figure 8 that the antennas 1-4 (four real elements and ten virtual elements in total) which can be divided into the first sub-array. And the antennas 2-5 can be divided into the second sub-array and so on. Using this sub-array divided technique, the 12-elements array can be divided into nine sub-arrays.
# Antenna Designs for 5G/IoT and Space Applications
## 2 Short Presentation of the Papers
Its features, including flexibility, bi/omnidirectional radiation pattern, planar structure, wide bandwidth covering Sub6 GHz and WLAN bands, and high inter-elemental isolation make it a good candidate for use on smartphone applications. The proposed antenna consists of one contacting ground at the center placed on the top of a flexible polyamide substrate and four conducting MIMO elements (Radiators) at the four corners on the top of the substrate. The proposed antenna has a total size of 70 mm \(\times\) 145 mm \(\times\) 0.2 mm, a wide impedance bandwidth ranging from 2.37 to 5.85 GHz, gain of 4-5.5 dBi, efficiency of 85% and self-isolation of about 17.5 dB. [PERSON] et al. [13] presented a wide-band dual concentric phase gradient modulated surface (PGMS) for surface radar cross-section (RCS) reduction at wideband frequency range, 20.9-45.7 GHz (75%). The main idea is using the two single band concentric modulated surfaces, e.g., MS1 and MS2 to reduce the RCS from 20.5-32 GHz (45%) for MS1 and 31.8-46.5 GHz (40%) for MS2, consequently. To enhance the bandwidth, the authors placed MS2 in the central part of MS1 to obtain a concentric configuration and hence achieve a wideband 75% (20.9-45.7 GHz) RCSR performance. [PERSON] et al. [14] designed a quad-port antenna MIMO antenna array for 5G smartphone applications. The proposed antenna array consists of four elements printed on two side boards, which are positioned vertically to the 150 mm \(\times\) 75 mm main board. The total size of the main board is 150 mm \(\times\) 75 mm \(\times\) 0.8 mm, and the size of the side boards is 150 mm \(\times\) 6.2 mm \(\times\) 0.8 mm. Each single element has a size of 14.9 mm \(\times\) 7 mm \(\times\) 0.8 mm and includes an L-shaped feed, a strip, a parasitic rectangular strip and a \(Z\)-shaped radiation strip that is connected to ground plane. The main idea of printing the quad-port antenna array along two long frames of the smartphones is to reserve space for 2G/3G/4G antennas. Parametric analysis had been completed by the authors to obtain the required results and the optimal dimensions of the proposed antenna array design. The proposed design achieved a dual band operation at 3.5 GHz (3.4-3.6 GHz) and at 5 GHz (4.8-5 GHz). The authors reported a measured efficiency of 82%, isolation of 16.5 dB, and total measured gains of 4.7 and 5 dBi at 3.6 and 5 GHz, respectively. Conceptualization, F.T., L.M. and R.R. ; methodology, F.T. ; validation, L.M. and R.R. ; investigation, R.R., F.T. and R.R. ; resources, F.T., L.M. and R.R. ; writing--original draft preparation, F.T. ; writing--review and editing, L.M. and R.R. ; visualization, F.T., L.M. and R.R. ; supervision, F.T. ; project administration, F.T., L.M. and R.R. All authors have read and agreed to the published version of the manuscript. This research received no external funding. The authors declare no conflict of interest.
# Estimation of Driving Direction of Traffic Accident Vehicles for Improving Traffic Safety
## 3 Proposed Method
### Problem Definition  
All roads have both Northbound and Southbound lanes, and depending on the environment of the road, traffic accidents can occur more frequently in specific directions. In Figure 2, the cars in the Southbound direction can drive without any problem. Conversely, in the Northbound direction, unpaved roads can serve as potential factors leading to traffic accidents. On paved roads, drivers rely on their line of sight to confirm the presence of vehicles on unpaved roads and make a right turn. Similarly, on unpaved roads, drivers must rely solely on their line of sight to merge onto paved roads. If obstacles obstruct the line of sight, such as trees, seeing other vehicles on different roads can be challenging.  
To prevent traffic accidents, departments in charge of road safety, such as the police, need to analyze which direction traffic accidents are more likely to occur based on the  
Figure 1: Overall procedure of proposed method.  
Figure 2: Accident risk case.  
environmental conditions in the Northbound and Southbound directions. Some countries, such as the North Carolina Department of Transportation's Division of Motor Vehicles in the United States, record the directionality of traffic accidents based on compass direction (east-west-south-north) [27]. On the other hand, some countries, including Korea, do not collect such directional information; they only collect data such as the date, location, environmental conditions, description, type, and cause of the occurrence in order to collect statistics necessary for developing traffic safety measures and assessing the risk of traffic accidents. In these countries, as there is no policy requirement to collect directional data, there is a need to estimate the directionality from the available information in other fields being collected.
###### Abstract  
With the rapid development of Earth observation technology, how to effectively and efficiently detect changes in multi-temporal images has become an important but challenging problem. Relying on the advantages of high performance and robustness, object-based change detection (CD) has become increasingly popular. By analyzing the similarity of local pixels, object-based CD aggregates similar pixels into one object and takes it as the basic processing unit. However, object-based approaches often have difficulty capturing discriminative features, as irregular objects make processing difficult. To address this problem, in this paper, we propose a novel superpixel-based multi-scale Siamese graph attention network (MSGATN) which can process unstructured data natively and extract valuable features. First, a difference image (DI) is generated by Euclidean distance between bitemporal images. Second, superpixel segmentation is employed based on DI to divide each image into many homogeneous regions. Then, these superpixels are used to model the problem by graph theory to construct a series of nodes with the adjacency between them. Subsequently, the multi-scale neighborhood features of the nodes are extracted through applying a graph convolutional network and concatenated by an attention mechanism. Finally, the binary change map can be obtained by classifying each node by some fully connected layers. The novel features of MSGATN can be summarized as follows: (1) Training in multi-scale constructed graphs improves the recognition over changed land cover of varied sizes and shapes. (2) Spectral and spatial self-attention mechanisms are exploited for a better change detection performance. The experimental results on several real datasets show the effectiveness and superiority of the proposed method. In addition, compared to other recent methods, the proposed can demonstrate very high processing efficiency and greatly reduce the dependence on labeled training samples in a semisupervised training fashion.  
change detection; superpixel segmentation; graph attention network; remote sensing images +
Footnote †: journal: Applied sciences
## 6 Algorithms and Frameworks in Federated Learning
### Federated Stochastic Gradient
#### 6.2.3 Comparison with FedAvg  
While both FedSGD and FedAvg are techniques in FL that aim to aggregate local model updates, the primary distinction is the method of aggregation. FedSGD focuses more on gradient updates, sending these to the central server for aggregation. In contrast, FedAvg sends the model parameters themselves after local training. Essentially, while FedSGD is gradient-centric, FedAvg is model-centric in its aggregation approach.
# Management of Acute Life-Threatening Asthma Exacerbations in the Intensive Care Unit
## 3 Management of Acute Asthma Exacerbation
### Nebulised Bronchodilators  
Nebulised \(\beta 2\) adrenoceptor agonists (salbutamol/albuterol) are central to the treatment of acute asthma exacerbations of all severity as well as for day-to-day maintenance. \(\beta 2\) adrenoceptors are G-protein-coupled transmembrane receptors that exist predominantly in airway smooth muscle cells. They activate the enzyme adenylyl cyclase, which produces cyclic adenosine monophosphate (cAMP) that likely activates protein kinase A and modification of intracellular calcium concentrations. Differences in the activity of \(\beta 2\) agonists mediate the kinetics of how airway smooth muscle responds; for example, salbutamol directly activates the adrenoceptor, while salmeteorl interacts with a receptor-specific auxiliary binding site [23]. The first-line therapy for rapid bronchodilation requires the use of high-dose nebulised \(\beta_{2}\) agonists driven by either oxygen or air depending on the degree of hypoxemia. Patients with minimal response to the initial dose may require continuous or \"back-to-back\" nebulisation. Intravenous \(\beta 2\) agonists are reserved for those patients in whom the nebulised therapy cannot be used reliably or in those who require additional bronchodilation during extreme states and are discussed in detail in the later section. The adverse effects of \(\beta 2\) adrenoceptor agonists are well known and pharmacologically predictable. They primarily include tachycardia and tremor but also have effects on serumpotassium and glucose. These effects tend towards tolerance with continued exposure, although this is of little relevance in the acute exacerbation phase [24].