esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Interference Analysis and Dynamic Frequency Allocation
### Interference Analysis in the Worst Case
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Parameters** & **GO** & **LEO** \\ \hline Semimajor axis & 42,164.1 km & 7378.14 km \\ Eccentricity & 0 & 0 \\ Inclination angle & 0\({}^{\circ}\) & 90\({}^{\circ}\) \\ Right ascension of the ascending node & 57\({}^{\circ}\) & 277\({}^{\circ}\) \\ Argument of perigee & 0\({}^{\circ}\) & 0\({}^{\circ}\) \\ Time past perigee & 0 s & 0 s \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Orbital parameters of the GEO and LEO satellites. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Parameters** & **Notations** & **Value** \\ \hline Frequency band & \(f\) & 20 GHz (Ka) \\ Noise temperature of receive antenna & \(T_{\text{n}}\) & 290 K \\ Antenna efficiency & \(\eta\) & 55\% \\ Antenna diameter of the user & \(D_{\text{U}}\) & 0.4 m \\ Bandwidth of each beam & \(B\) & 10 MHz \\ Antenna diameter of GEO satellite & \(D_{\text{G}}\) & 0.6 m \\ Transmit power of GEO beam & \(P_{\text{G}}\) & 60 W \\ Antenna diameter of LEO satellite & \(D_{\text{L}}\) & 0.1 m \\ Transmit power of LEO beam & \(P_{\text{L}}\) & 2 W \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Parameters of the GEO and LEO systems. Figure 4: SINR versus \(l\) for GEO and LEO users.
# Bloom Filter Approach for Autonomous Data Acquisition in the Edge-Based MCS Scenario +
## 3 Materials and Methods  
This section describes an edge-based architecture for MCS and algorithms used to achieve autonomous data acquisition in such a distributed environment. More precisely, we first present an edge-based decentralized MCS ecosystem. Then, we give a brief overview of the Bloom filter data structure that we use to communicate existing sensor readings between data sources and edge MCS services. Then, we present an algorithm that runs on mobile devices and enables them to autonomously control the data acquisition process by monitoring their local filter structure and deciding whether a reading is valuable to the system or not. Finally, we outline the main algorithm procedures.
# Oscillation Suppression Method of Digital Proportional Valve Based on Fuzzy Intelligent PID Control
###### Abstract  
A digital proportional valve is constituted by the main spool and a high-speed on/off valve bridge acting as the pilot stage. However, the main spool will generate oscillation during movement under the control of the pilot stage. This results in poor stability, slow response speed, low control accuracy, and even the potential loss of control of the valve. To tackle this issue, an oscillation suppression method based on fuzzy intelligent proportional-integral-derivative (PID) control is put forward. The movement state of the main spool is determined in accordance with its movement position and velocity. Thereafter, the fuzzy control parameters of the controller are calculated on the basis of the determined movement state of the main spool. Different PID parameters are adopted to eliminate the control effect difference caused by the structural asymmetry of the two pilot control chambers of the main valve. The performance and robustness of the proposed control method are verified by comparison with the PID controller based on full-bridge and half-bridge control. The results demonstrate that the proposed control method can effectively suppress the oscillation of the main spool of the digital proportional valve, improve the control accuracy, and reduce the response time. When the excitation signal takes the form of a step signal, the overshoot of the control method put forward in this paper is diminished by 26.2% in comparison with that of the PID control. Under stable operating conditions, the maximum tracking error is less than 3.1%. Moreover, compared with simply using the PID control method, this error is reduced by 41%.  
fuzzy intelligent PID control; digital proportional valve; oscillation suppression; high-speed on/off valve bridge
# Towards the Development of Agenda 2063 Geo-Portal to Support Sustainable Development in Africa
## 3 Geoportal Implementation Framework
### Implementation of the Web Front-End: Geospatial Services  
The Agenda 2063 Geoportal aims to provide a wide range of client geospatial web services to African countries. Key among them is the ability to discover, visualize, access, retrieve, compare, and download spatial data sets related to agenda 2063 goals. To build the front-end of the geoportal we integrated map service, feature service, and image service functionality into the web interface. The processes for data access and retrieval are depicted in Figure 2 above. As depicted in the flow chart above, various operations are supported by the web application front end. A selection operation for a country of interest is illustrated where a user click is used to query the database and return a country of interest. Similar operations are supported for selecting and displaying country indicators and statistical information that is then analysed and compared by various charting options provided by the front end.  
Three levels of user access were defined in the design of the geoportal. The general user access level is aimed at the general public. At this level, users can use some of the most basic functionality of the geoportal which includes visualization of the geospatial datasets available on the portal. The general public is required to register and login to access additional geospatial services, such as charting for comparing development data from countries and regions. To protect the integrity of some sensitive datasets, access rights are validated using a filter once a user has logged in. User rights are administered by the national statistical offices. The data administrators are responsible for data verification, data uploading, and data integrity and data access in their own countries. A system administrator is assigned responsibility for managing the computer systems, web pages, databases, security threats, and the environment where the system is operating.  
Since MapServer was utilized in achieving data interoperability, through OGC data sharing standards, datasets can be served to third-party visualization platforms such as QGIS and ArcMap by WMSs. When the user requests data from the portal, the portal first validates the user access rights and once permission has been granted the data is retrieved from the host server database and sent back to the user. The retrieval process is in line with the Open Geospatial Consortium[i] standard for web mapping as shown in Figure 3 below.
# Globally Optimizing QAOA Circuit Depth for Constrained Optimization Problems
## 2 Materials and Methods
### Global Variable Substitution
#### 2.5.3 Example: Global Variable Substitution  
To give an example of the GVS method, we will apply it to the product formulation of Example 1. We want to decompose the three-variable terms into two-variable terms by substituting a new variable to represent the product of the variables. In order to do so, we first choose substitutions and then create the derived graph. For Example 1, we substitute \(x_{1}x_{3}=u_{1,3}\) and \(x_{2}x_{5}=u_{2,5}\). Thus, the first clause, which can be written as \(x_{3}-x_{2}x_{3}-x_{1}x_{3}+x_{1}x_{2}x_{3}\) is equal to \(x_{3}-x_{2}x_{3}-u_{1,3}+u_{1,3}x_{2}\). With the substitution \(x_{1}x_{3}=u_{1,3}\), the edge \(x_{1}x_{3}\) is already accounted for in the first constraint. We then need only add the edge between \(x_{2}\) and \(x_{3}\) to the derived graph since the monomial \(x_{2}x_{3}\) exists in the expansion of the first clause. Note that each clause can be decomposed similarly and will end up with a sum of terms, at least one of which contains three variables, with the others containing one or two depending on the number of \((1-x_{i})\) expressions. The other edges that need to be added due to the two variable terms in the expansions are \(x_{1}x_{4}\), \(x_{3}x_{4}\), \(x_{1}x_{2}\) and \(x_{2}x_{4}\). See Table 1 for the contribution of unsubstituted monomials from a particular clause to \(\deg_{c}(x_{i})\) for a generic substitution \(x_{p}x_{c}=u_{b,c}\). The increase in degree ranges from 0 to 2, with the maximum addition being \(k-1\) for general \(k\)-SAT.  
Next, we list each constraint of the form Equations (7) and (8) and dualize them. For the first clause \(c=1\) in the example,  
\[u_{1,3} =x_{1}+x_{3}+\delta_{1,1}\] \[u_{1,3} =x_{1}+\delta_{1,2}\] \[u_{1,3} =x_{3}+\delta_{1,3}.\]  
When dualizing these constraints, the terms  
\[(u_{1,3}-x_{1}-x_{3}-\delta_{1,1})^{2} =u_{1,3}+x_{1}+x_{3}+\delta_{1,1}-u_{1,3}x_{1}-u_{1,3}x_{3}-\] \[u_{1,3}\delta_{1,1}+x_{1}\delta_{1,1}+x_{3}\delta_{1,1}+x_{1}x_{3} \tag{12}\] \[(u_{1,3}-x_{1}-\delta_{1,2})^{2} =u_{1,3}+x_{1}+\delta_{1,2}-u_{1,3}x_{1}-u_{1,3}\delta_{1,2}+x_{1 }\delta_{1,2}\] (13) \[(u_{1,3}-x_{3}-\delta_{1,3})^{2} =u_{1,3}+x_{3}+\delta_{1,3}-u_{1,3}x_{3}-u_{1,3}\delta_{1,3}+x_{3 }\delta_{1,3} \tag{14}\]  
are added to the objective function, up to constant \(\lambda\), and similar terms are added for the \(u_{2,5}\) substitution. Since all variables, \(v\), in the equations above have the value zero or one, \(v^{2}=v\). The entire derived graph can be seen in Figure 6. Note that the degrees match the theorem plus the number of edges induced by pairs that are not substituted. The largest degree vertex is \(x_{2}\), which has degree eight, so the unitary circuit depth for one layer of QAOA is either nine or ten. This is less than the unitary circuit depth for the linear 3-SAT formulation and requires fewer ancillary qubits.
## 2 Study Area and Data  
### Study Area  
The metropolitan city of Seoul was selected as the study area. Seoul is located in the center of the Korean Peninsula and is the country's capital. Its area is 0.6% (605 km\({}^{2}\)) of the total area of Korea, but the population density is very high at 16,100 people/km\({}^{2}\). Due to this high population density, the traffic volume is also extremely high, road safety is diminished, and the road safety index is low [13].  
Seoul city has 80.6 rainy days with over 1.0 mm rainfall per year on average, and the average annual rainfall of Seoul city is 1387 mm, which is 28.9 mm higher than the average for Korea, according to the data from the Korea Meteorological Administration. Due to the recent extreme weather, the rainfall deviation in each administrative area, including that in Seoul, is large. Therefore, it is necessary to analyze the relationship between traffic accidents and the rainfall in Seoul using appropriate rainfall information.
## 3 Results
### Analysis of Spatiotemporal Movement Patterns
The following results can be drawn from Figure 7 and Table 3:  
* Analyzing the annual change rate of the north-south component of the baseline, the baseline in the north-east direction is mainly shortened, with a mean annual change rate of \(-2.7\) mm/y, concentrated in the western and northern areas of Sichuan. The bottom graph shows that the movement of the plates in the region is smoother in the north-south direction. Some of the baselines in the north-west direction are in a stretching state, with a mean annual rate of change of \(2.0\) mm/y, concentrated in the south-central part of Sichuan. The more intense plate motions in the region may be one of the reasons for the baseline stretching. * The annual rate of change of the east-west component of the baseline is analyzed, and a large number of baselines in the north-east direction are shortening year by year, concentrated in the central and northern areas (68%), with a mean annual rate of change of \(-3.0\) mm/y. The bottom graph shows that the movement of the plates in the region is smoother in the east-west direction, which may have caused the baseline stretching. Some baselines in the north-west and north-east directions are mainly in a stretching trend, with a mean annual rate of change of \(2.7\) mm/y. * The annual rate of change of the vertical component of the baseline was analyzed and 68% of the baseline showed a shortening trend characteristic with a mean annual rate of change of \(-1.4\) mm/y. A small number of baselines were in a stretched state with a mean annual rate of change of \(1.1\) mm/y. As can be seen from the bottom graph, the shortened baselines are mainly concentrated in the subsidence area, indicating that ground subsidence may cause baseline shortening in the Sichuan region. * From the annual rate of change in the shortening trend baseline, the vertical component is \(1.3\) mm/y and \(1.6\) mm/y lower than the north-south and east-west components, respectively. From the annual rate of change in the stretching trend baseline, the vertical component is \(0.9\) mm/y and \(1.6\) mm/y lower than the north-south and east-west components, respectively, showing a more stable baseline in the vertical direction. * Analyzing the annual rate of change of baseline lengths, the baselines in the north-west direction are mainly dominated by a shortening trend, with a mean annual rate of change of \(-2.8\) mm/y, showing that these baselines are shortened on a scale of \(2.8\) mm per year; some of the baselines in the north-east and north-west directions are dominated by a stretching trend, with a mean annual rate of change of \(2.6\) mm/y, with more obvious changes. From the bottom graph, it can be seen that the topography of Sichuan gradually declines from northwestern to southeastern, and the baseline of scale shortening is mainly concentrated in the region with relatively smooth topog
# Water Extraction in PolSAR Image Based on Superpixel and Graph Convolutional Network
## 3 Results
### Results of Study Area 1
#### 3.2.4 Classification Results  
A small area is shown in Figure 9 to visualize the superpixels and constructed graph data. To highlight the performance of GNN, classifiers of RF and XGBoost were also used to classify the superpixels based on the selected features. Results show that they all achieved good visual performance (see Figure 10a-c) relative to the ground truth (see Figure 10g). To validate the effectiveness of superpixels, standard TS, RF, and XGBoost were also tested on the dimension of pixels. All pixels in 46 water superpixels and 67 non-water superpixels (the same as in the superpixel classification) were used for training, and all other pixels in the image (with labels) were used for validation. The results can be seen in Figure 10d-f. Pixel-based methods produced much more noise than superpixel-based methods, and  
Figure 7: (**a**) Feature relevance (Tau denotes texture); (**b**) the top five most important features.  
standard TS had the worst performance. Of course, extra filter operations could improve the results to some extent, but in this research, we merely discuss standard processing.  
Quantitative evaluations are given in Table 1. Both superpixel-based and pixel-based methods were tested, and scores were calculated in their own dimensions. To compare our method's results with pixel-based methods, the scores should be recalculated again from the superpixel-level to pixel-level according to their spatial inclusion relations (see the last line of Table 1). Results show that our method had the highest precision, recall, and F1 scores. For superpixel-based methods, the recall score of our method was 3 to 4 percent higher than RF and XGBoost. XGBoost obtained the second-best scores. We also tested another graph convolution network called GAT [42], whose performance was worse as well. To further visualize the difference between XGBoost and GNN, regions of TP (true-positive), FN (false-negative), and FP (false-positive) are presented in Figure 11. We can see that XGBoost missed many positive superpixels in small water areas or the boundary of land-water areas. A GNN can deal with this problem better due to its powerful ability to  
Figure 8: (**a**) Visualization of features after t-SNE operation—three classes were acquired; (**b**) pre-classification result through K-Means.  
Figure 9: Constructed graph data from image. (**a**) Superpixels on the PolSAR image; (**b**) visualization of graph data.  
capture contextual information. The second part of Table 1 clearly shows that our proposed method achieved much higher scores than pixel-based RF and XGBoost.
# Enzymatic Synthesis of Biobased Polyesters and Polyamides
## 6 Enzyme-Catalyzed Synthesis of Polyesters  
Enzymatic polymerization is defined as \"in vitro (in the test tubes) chemical synthesis of polymers via a non-biosynthetic (non-metabolic) approach using an isolated enzyme as the catalyst\" [(199; 36)]. Due to the unique properties of enzymes, enzymatic polymerization inherits many merits such as high specificity and selectivity towards monomer substrates, clean-process, energy saving, gentle environmental footprint, nontoxic natural catalysts, and recyclable catalysts (after immobilization). With these, enzymatic polymerization provides an opportunity to achieve \"green polymer chemistry\". At present, 4 enzyme classes, oxidoreductase, transferases, hydrolases and ligases, are identified to induce or catalyze polymerizations (Table 3) [(200)]. Many polymers are successfully synthesized via enzymatic polymerizations, for example, vinyl polymers [(201; 38)], polysaccharides [(202; 203; 204; 205)], polyesters [(44; 42)] and polyamides [(206; 207; 208)]. Among them, polyesters are the most extensively studied polymers in enzymatic polymerization; and lipases are the most efficient biocatalysts for enzymatic polymerization of polyesters [(42)]. Generally speaking, three polymerization modes can be proceeded for the lipase-catalyzed polyester synthesis (Scheme 12): (1) step-growth polycondensation; (2) ring-opening polymerization; and (3) a combination of ring-opening polymerization and polycondensation (ring-opening addition-condensation polymerization). Among them, polycondensation and ring-opening polymerization are the most common methods used for biocatalytic polyester synthesis. Four modes of elemental reactions may occur during the lipase-catalyzed polyester synthesis, inducing hydrolysis, esterification, transesterification (alcoholysis and acidolysis), and intereesterification (Scheme 13). These reactions are all reversible. Therefore, to facilitate the ester formation, it is crucial to remove the remaining water and byproducts like alcohols from the reaction mixture, for example, by adding absorbing and drying agents like molecular sieves, applying reduced pressure, using azeotropic distillation conditions, and so on. The first lipase-catalyzed polymerization was reported by [PERSON] et al. in 1984 [(209)]. They investigated the enzymatic polymerization of aliphatic diacids and diols by a lipase from _Aspergillus niger_ NRRL 337 (Scheme 14). However, only oligoesters with \(\overline{M_{n}}\)'s of around 1000 g/mol were obtained.
## 3 Methodology
### Adaptive Controller Design with Input Saturation
\tag{58}\]  
Then, from (55)-(57), we obtain  
\[ \begin{cases}\dot{v}_{c}=-k_{3}v_{c}+[(\dot{\alpha}_{2}^{c}-\dot{\alpha}_{2}^ {co})+z_{2}]\\ \dot{z}_{2}=-k_{4}z_{2}+M_{3}[(\dot{\alpha}_{3}^{c}-\dot{\alpha}_{3}^{co})+z_{ 3}]-v_{3}\\ \dot{z}_{3}=-k_{5}z_{3}+M_{3}D_{2}-M_{3}v_{4}\end{cases} . \tag{59}\]  
Step 1: According to (49)-(51), a Lyapunov function is designed:  
\[V_{3}=\frac{1}{2}(v_{3}^{2}+v_{4}^{2}+v_{5}^{2}). \tag{60}\]  
The derivative of \(V_{3}\) is  
\[\dot{V}_{3}=v_{3}\dot{v}_{3}+v_{4}\dot{\alpha}_{4}+v_{5}\dot{v}_{5}\leq-k_{3}v _{3}^{2}-k_{4}v_{4}^{2}-k_{5}v_{5}^{2}\leq-n_{3}V_{3}, \tag{61}\]  
where \(n_{3}=2\text{min}\{k_{3},k_{4},k_{5}\}_{k_{3}}>0,k_{4}>0,k_{5}>0\). Multiply both sides of (61) by \(e^{n_{3}t}\), and then integrate both sides to obtain the following:  
\[V_{3}(t)\leq V_{3}(0)e^{-n_{3}t}\leq V_{3}(0). \tag{62}\]  
Additionally, then we can determine that \(|v_{i}|\leq B_{3}\), \(i=3,4,5\), \(B_{3}=\sqrt{2V_{3}(0)}\). This indicates that \(v_{3}\), \(v_{4}\), and \(v_{5}\) converge to \(\Omega_{3}:=\{v_{i}\in R,i=3,4,5||v_{i}|\leq B_{3}\}\). Step 2: Consider a Lyapunov function candidate:  
\[V_{4}=\frac{1}{2}(\dot{v}_{c}^{2}+\dot{z}_{2}^{2}+\dot{z}_{3}^{2}). \tag{63}\]  
The derivation of equation (63) is provided by  
\[ \begin{array}{l}\dot{V}_{4}=(v_{c}\dot{v}_{c}+z_{2}\dot{z}_{2}+z_{3}\dot{z}_ {3})\\ \leq-(k_{3}-1)v_{c}^{2}-(k_{4}-M_{3}-1)z_{2}^{2}-(k_{5}-1.5M_{3})z_{3}^{2}\\ +\frac{1}{2}|l_{1}\theta|^{2}+0.5M_{3}|l_{1}\theta|^{2}+\frac{1}{2}M_{3} \overline{D}_{2}^{2}+\left(\frac{1}{2}+\frac{1}{2}M_{3}\right)B_{3}^{2}\\ \leq-n_{4}V_{4}+\delta_{4}\end{array} , \tag{64}\]  
where \(n_{4}=2\text{min}\{k_{3}-1,k_{4}-M_{3}-1,k_{5}-1.5M_{3}\}\), \(k_{3}-1>0\), \(k_{4}-M_{3}-1>0\), and \(k_{5}-1.5M_{3}>0\). \[\delta_{4}=\frac{1}{2}|l_{1}\theta|^{2}+0.5M_{3}|l_{1}\theta|^{2}+\frac{1}{2} M_{3}\overline{D}_{2}^{2}+\left(\frac{1}{2}+\frac{1}{2}M_{3}\right)B_{3}^{2}.\]  
Multiply both sides of (64) by \(e^{n_{4}t}\), and then integrate both sides to obtain the following:  
\[V_{4}(t)\leq V_{4}(0)e^{-n_{4}t}+\delta_{4}(1-e^{-n_{4}t})/n_{4}\leq V_{2}(0)+ \delta_{4}/n_{4}. \tag{65}\]  
Additionally, then we can determine that \(|v_{c}|\leq B_{4}\), \(|z_{2}|\leq B_{4}\), \(|z_{3}|\leq B_{4}\), and \(B_{4}=\sqrt{2V_{4}(0)+2\delta_{4}/n_{4}}\). This indicates that \(v_{c}\), \(z_{2}\), and \(z_{3}\) converge to a compact set: \(\Omega_{4}:=\{v_{c},z_{2},z_{3}\in R,\)\(||v_{c}|\leq B_{4},|z_{2}|\leq B_{4},|z_{3}|\leq B_{4}\}\). \(\square\)
# Shunt Damping Vibration Control Technology: A Review
## 3 Passive Shunt  
The passive shunt mainly utilizes passive electronics, such as a resistor, a capacitor, and an inductor. Single mode and multimode vibration control can be achieved by designing the external shunt circuit. Piezoelectric and electromagnetic transducers are complementary with each other, which means that the series resonant shunt for the piezo is comparable to the parallel shunt of the electromagnet (and vice versa). In general, damping of dominant vibration modes of a flexible structure and their efficiency relies very much on the precise choosing of the shunt components. This section summarizes these linear shunts and calibration process.
# Estimating Interception Density in the BB84 Protocol: A Study with a Noisy Quantum Simulator
###### Abstract
Indeed, the accurate detection of an eavesdropper would allow for more efficient use of the expensive quantum resources involved in QKD, ultimately enhancing the overall security and effectiveness of key-sharing processes. The intercept-and-resend attack is widely recognized as a strategy employed by eavesdroppers within the BB84 protocol [12]. The study of this approach has led to a practical eavesdropping method known as a partial intercept-and-resend attack [13; 14], where the eavesdropper intercepts a qubit with probability \(p\) (also referred to as the interception rate or density) and leaves it untouched with probability \((1-p)\). Such an attack represents one of the simplest individual attacks by an eavesdropper. For simplicity and clarity in analyzing eavesdropper detectability in the QKD protocol, this paper assumes the partial intercept-and-resend attack as the sole strategy employed by the eavesdropper. Previous studies have calculated the quantum bit error rate (QBER) under the partial intercept-and-resend attack with rate \(p\) in the BB84 protocol as \(p/4\)[15]. This calculation considers the error due to eavesdropping independently of the error introduced via quantum system noise. This paper extends the previous analysis by examining the QBER of the partial intercept-and-resend attack in the BB84 protocol as a function of errors generated via quantum system noise. Therefore, this comprehensive analysis, in conjunction with the simulation validation, aims to provide a more realistic understanding of QBER behavior by incorporating the imperfections inherent in practical QKD systems.