esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Approaches of Optimizing Geolocation Measurements
### Artificial Intelligence (AI)
#### 4.5.1 Genetic Algorithm (GA)  
In the geolocation field, Genetic Algorithms (GA) have been developed to overcome the drawbacks of geolocation algorithms in traditional methods. In the early 1970s, [PERSON] introduced the concept of GA. There are two requirements to define a typical genetic: a genetic representation and fitness function; (i) A genetic representation of the solution domain, and (ii) a fitness function to evaluate the solution domain. GA can be represented by a sequence of procedural steps for moving from one population of chromosomes (by artificial intelligence) to a new population. Each chromosome consists of some genes. Each gene may be represented by binary strings, real numbers, permutations of an element, or a program element (genetic programming) [92]. In [95], for the first time, the authors implemented a GA based on TDOA measurements in Taiwan. They achieved noted improvement in the accuracy of geolocation. This study considered five monitoring stations distributed in 3D as A = (0 km, 0 km, 0 m), B = (10 km, 10 km, 100 m), C = (10 km, 10 km, 100 m), D = (0 km, 10 km, 100 m), and E = (10 km, 0 km, 0 m). The experiment result showed that the measurement error decreased when the number of monitoring stations increased. When the NLOS is considered, the results showed that the geolocation accuracy at a circular error probability of 50% was less than 60 m. Moreover, the proposed algorithm yielded 17-fold and 19-fold improvement when the emitter location was favourable and unfavourable compared to the hyperbolic calculations based on conventional TDOA measurements.
# The Development of a Spaceborne SAR Based on a Reflector Antenna
## 3 Reflector Antenna Configurations in Spaceborne SAR Systems
### Deployable Antenna
#### 3.1.3 Radial Rib Deployable Antennas  
Radial rib deployable reflector antennas, also known as star-rib antennas, are a well-established configuration widely used in spaceborne systems [34; 54; 55]. Structurally similarly to an umbrella, they comprise multiple curved carbon-fiber parabolic ribs attached to a central hub, supporting a metal mesh reflector. When stowed, the ribs fold along the central axis. During deployment, motors drive the ribs to unfold radially around the hub. The reflective mesh is tensioned by a cable-net structure stretched over the deployed ribs. When retracted, the ribs fold inward via a base mechanism into a compact cylindrical shape. Once deployed, the antenna resembles a fully opened umbrella, as illustrated in Figure 9a. This configuration uses a centralized mechanism to deploy ribs radially, forming the reflector surface through interconnecting cables. It offers a simple structure, reliable deployment, and low weight, making it suitable for large spaceborne antennas and promising for SAR applications.  
For example, Israel's TecSAR satellite, launched in 2008 [14; 56], adopts a radial rib antenna and employs mosaic scanning, combining electronic and mechanical methods to achieve high-resolution imaging across wider coverage areas (see Figure 9b). India's RISAT-2 series, launched by ISRO in 2009, also uses radial rib antennas and supports multiple imaging modes. Japan's QPS-SAR, launched in 2019, features a 3.6-m diameter antenna that folds into a compact 0.8-m diameter and 0.15-m height. In 2024, China's Neptune-01 was launched with a radial rib deployable reflector antenna for use in resource monitoring, disaster management, environmental protection, and maritime security.  
Figure 8: Perimeter truss deployable antenna: (**a**) deployment process [52]; (**b**) NISAR satellite [16]; (**c**) Tandem-L satellite [53].
# An Improved PSO Algorithm and Its Application in GNSS Ambiguity Resolution
## 3 Experiments and Result Analysis
### Performance Analysis of IPSO-AR
The computer processor used in our experiment is Intel(R) Pentium(R) CPU [EMAIL_ADDRESS] GHz with 4.0 G RAM. All computer programs used standard C language. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Experiments**} & \multicolumn{5}{c}{**DD Float Ambiguity**} & \multicolumn{2}{c}{**Parameter Setting**} \\ \cline{2-7}  & & **Epochs** & **ADOP** & **Precision** & \(n\) & \(s\) \\ \hline \multirow{3}{*}{Scheme \#1} & P1 & & & & 30 & 10 \\  & P2 & 10 & (0,0.1) & High & 60 & 20 \\  & P3 & & & & 90 & 30 \\ \hline \multirow{3}{*}{Scheme \#2} & P1 & & & & 30 & 10 \\  & P2 & 5 & (0.1,0.5) & General & 60 & 20 \\  & P3 & & & & 90 & 30 \\ \hline \multirow{3}{*}{Scheme \#3} & P1 & & & & 30 & 10 \\  & P2 & 1 & (0.5,2) & Low & 60 & 20 \\ \cline{1-1}  & P3 & & & & 90 & 30 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Experimental design with various precision double differenced float ambiguities and parameter setting. DD: double differenced; ADOP: ambiguity dilution of precision. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Dimension** & \(N\) = 3 & \(N\) = 4 & \(N\) = 5 & \(N\) = 6 & \(N\) = 7 \\ \hline Frequency & L1 & L1 & L1 & L1 & L1 + B1 \\ DD Sat & 3G & 4G & 5G & 6G & 6G + 1B \\ \hline
**Dimension** & \(N\) = 8 & \(N\) = 9 & \(N\) = 10 & \(N\) = 11 & \(N\) = 12 \\ Frequency & L1 + B1 & L1 + B1 & L1 + B1 & L1 + B1 & L1 + B1 \\ DD Sat & 6G + 2B & 6G + 3B & 6G + 4B & 6G + 5B & 6G + 6B \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Frequency and satellite information with various DD ambiguity dimensions.
## 4 Conclusions  
We have qualified the UNPS as an apparatus that can measure particle size and concentration during a liquid phase bottom-up synthesis of silica nanoparticles starting from molecular precursor:  
* With static measurements we have verified the UNPS' ability to measure particle size accurately enough by comparing the results of the UNPS and TEM. The UNPS and TEM measurements were mostly in the 3\(\sigma\) ranges.
* With static measurements we have verified the UNPS' ability to measure particle concentration accurately enough by comparing the UNPS results with the drying measurements. The mass  
Figure 8: **(a)** The mean diameter of the Silica particles measured by the UNPS (blue), TEM (red), and dynamic light scattering (DLS) (yellow), during the Stöber reaction. **(b)** The mass percentage of the Silica particles measured by the UNPS during the Stöber reaction.  
concentration measurements showed good consistency between the undiluted, the half diluted samples, and the drying measurements. Concentrations below 2.5 w % were less consistent. However, most samples were within 14% of their expected value.
* One UNPS measurement every minute was fast enough to follow a Stober reaction for the synthesis of silica nanoparticles in real-time.  
We are convinced that with this qualification the UNPS is a good addition to the particle measurement toolset and can be used in a complementary way with currently existing methods. Implementation of the method will help the industry to improve the design and production of nanoparticles.  
[PERSON], [PERSON], [PERSON], [PERSON], and [PERSON] conceived and designed the experiments; [PERSON] and [PERSON] performed the experiments; [PERSON], [PERSON], and [PERSON] analyzed the data; [PERSON] contributed to the interpretation of the analyses results; [PERSON], [PERSON], [PERSON], and [PERSON] built the UNPS software; and [PERSON] and [PERSON] wrote the manuscript. All authors have read and approved the final manuscript.  
This work was supported by the European Commission and is part of the EU project COPILOT which has received funding from the European H2020 program under grant agreement n\({}^{\circ}\) 645993. Solliance and the Dutch province of Noord Brabant are acknowledged for funding the TEM facility.  
The authors declare no conflict of interest.
# On the Secrecy Sum-Rate of Internet of Things Networks: Scheduling and Power Control +
## 6 Discussion  
In this section, we discuss the possible extensibility of our analysis and proposed scheme to various applications such as satellite communications and IoT networks.
## 4 Methodology
### Source Selection and Approach  
An extensive exploration was undertaken utilizing various popular databases and search engines to gather pertinent research material for this review. Three popular databases (Scopus, Google Scholar, and PubMed) renowned for their comprehensive coverage were used to search for scholarly works on the subject. The search strategy was based on the above search criteria. A time constraint was applied, restricting the search to include articles published between 2019 and 2023.  
Most of the papers reviewed are journal articles or conference papers. They were selected on the basis of the quality of the journal and relevance to the topic and filtered by date of publication. The selection of articles is based on titles relevant to the topic of this review. The initial search for the above search criteria (C1-C4) found 556 references from Scopus, 565 references from Google Scholar, and 198 references from PubMed. However, the total number of references, 1319, was reduced to 280 after eliminating duplicates and incomplete references. Further screening of the title, abstract, and full text allowed the elimination of 182 references that addressed issues far from the main topic of this review article. The final number of references eligible for this study was 98. These references do not include the references we cited in the background sections.
## 5 The SDRE Integral Type Servo Controller
### Design of SDW Matrix
#### 5.3.3 Design of SDW Matrix-Cooperative Control of RW and DRC Antenna
\begin{split} Q_{q_{e_{n}}}=& 1/(1+\exp(-10^{3}(|\omega_{r_{n}}|-0.01))) \left(10+(10^{8}-10)(1/(1+\exp(-10^{3}(|q_{e_{n}}|-0.1))))\right)\\ &+\left(1-(1/(1+\exp(-10^{3}(|\omega_{r_{n}}|-0.01))))\right)10^{8 }K_{Q(q_{e_{n}}\mathbf{\omega}_{r_{n}})}\ \ (n=1,2,3)\\ Q_{q_{e_{n}}}^{int}=& 1/(1+\exp(-10^{3}(|\omega_{r_{n}}|-0.01))) \left(10^{8}-(10^{8}-10)(1/(1+\exp(-10^{3}(|q_{e_{n}}|-0.1))))\right)\\ &+\left(1-(1/(1+\exp(-10^{3}(|\omega_{r_{n}}|-0.01))))\right)10^ {8}K_{Q(q_{e_{n}}\mathbf{\omega}_{r_{n}})}\ \ (n=1,2,3)\end{split}  \tag{45}\]  
We carry out the simulation II using SDRE servo controller the SDW matrix of which is shown in Equations (45) and (46). And, we show the results in Table 6 and Figure 11. From Table 6, we can confirm that proposed method SDW matrix of which is shown in Equations (45) and (46) can reduce settling time compared with SDRE and SDRE servo the SDW matrix of which is fixed. This is because proposed method SDW matrix of which is shown in Equations (45) and (46) can reduce the overshoot compared with SDRE servo controller. However, the steady state error occurring from 20 s to 38 s when RW wheel speed reach the limit of it adversely affects attitude maneuver. Therefore, we design a cooperative control method to reduce the steady error caused by RW reaching performance limit. We design the cooperative control method so that the antenna motor generates torque for satellite attitude maneuver when RW reaches the limit of RW wheel speed. From Equation (28), we can confirm that we can take the reaction torque generated by antenna motion into consideration in the SDLR. Thus we can mention that by making \(\mathbf{Q}_{q_{e}}\) quite larger than \(\mathbf{Q}_{\phi_{e}}\) the antenna motor gives priority to reducing the satellite angle error rather than reducing the antenna angle error. In addition, by making \(\mathbf{R}_{\hat{\Omega}}\) larger than \(\mathbf{R}_{\tau_{\phi}}\) antenna motor can generate the torque for satellite attitude maneuver instead of RW. Accordingly, in order to make the antenna motor generates torque for satellite attitude maneuver when RW reaches the limit of RW wheel speed we design the SDW matrix \(\mathbf{Q}_{\phi_{e}},\mathbf{R}_{\hat{\Omega}}\) with the design guidelines as shown in Table 7 as follows:  
\[\mathbf{Q}_{\phi_{e}}=10^{4}+(10^{6}-10^{4})(1/(1+\exp(-10^{3}(|(|\Omega|)-\Omega^{ lim}|-20)))) \tag{47}\]  
\[\mathbf{R}_{\hat{\Omega}}=100-(100-10)(1/(1+\exp(-10^{3}(|(|\Omega|)-\Omega^{ lim}|-20)))) \tag{48}\]  
Accordingly, we design the SDW matrix as shown in Table 8.
## 3 Test Results and Analysis
### Conventional Triaxial Compression Strength  
#### 3.2.1 Stress-Strain Curve Characteristics  
The conventional triaxial compression stress-strain curves for gravel soil stabilized with different amounts of xanthan gum and lignin at various confining pressures are shown in Figure 4. In this context, \((\sigma_{1}-\sigma_{3})\) represents the principal stress difference. Similar to the unconfined compression tests, the inherent micropores of the specimen are compressed at initial low loading levels. As the load continues to increase, the specimen enters the linear elastic phase, with the curve approximately linearly rising. As the load continues to increase, the specimen reaches its yield strength and enters the plastic phase, where the stress-strain curve becomes nonlinear and the specimen fails in shear after reaching peak strength. In contrast to the unconfined compressive strength, the residual strength of the specimen remains relatively high under confining pressure (\(\sigma_{3}\)). The natural soil shows strain softening, whereas the strain in the xanthan gum and lignin-enhanced specimens shows a significant transition from a weak softening curve to a weak hardening curve. In addition, the failure mode shifts from brittle to plastic. The stress-strain curve in the elastic phase has a steeper slope for the improved soil. It is also observed that the higher the confining pressure, the less pronounced this phenomenon becomes, and the strain differences between natural and improved soils become smaller.  
Figure 3: Relationship between unconfined compressive strength and xanthan gum and lignin dosing.
## 2 Related Work
### System Composition
#### 2.1.1 UML-Based Proposals  
UML-based solutions provide a user-friendly representation of the system and are mainly covering the initial stages of the design phase. The Interaction Flow Modeling Language (IFML) [21], standardized by the Object Management Group [22], utilizes the main data types of the UML meta-model and meta-classes, and can model the user interfaces (UI) of IoT-based applications. The work in [23] utilizes IFML to further define design patterns for a set of common user interactions for incorporated applications. Exploiting the UML features and available tools, the abstract code for these interfaces can be also generated by the graphical designs. However, such solutions represent only static instances for a system and their ability to assess a dynamically composed settings is limited.
# Blind Compensation of \(I/q\) Impairments in Wireless Transceivers
## 2 Model Formulation and Mitigation Methodology
### Accuracy of Derived PDF
The reason being that the derived PDF does not consider the effects of noise and this results in a significant discrepancy between the two density functions. However, at around 12 dB SNR, the discrepancy reduces significantly and the KL divergence curve is close to the noiseless case (dotted line). Hence, the estimation of the imbalance signal is carried out using the derived PDF of \(\mathbf{y}_{R}\) without including the effects of noise as this leads to simplicity in the estimation procedure.
# AI-Assisted Security Alert Data Analysis with Imbalanced Learning Methods
## 2 Related Work
### Combating Data Imbalance  
The prevalence of benign network traffic events often causes the alert data generated by NIDS to be imbalanced, with more benign events than malicious ones. Studies have investigated methods for handling imbalanced issues using resampling, cost sensitivity, and clustering techniques.
# Numerical Simulation of Piles in a Liquefied Slope Using a Modified Soil-Pile Interface Model
## 4 Parametric Study  
A parametric study was conducted to analyze the effects of changes in the slope inclination and input motion amplitude on the displacement of the slope and the dynamic behavior of piles in liquefaction-susceptible slopes. The study utilized a validated numerical analysis model that was applied consistently. The slope inclination was varied using 12.5, 15.9, 18.4, 21.8, 29.1, and 33.7 degrees, while the input amplitude was varied using 0.05 g, 0.1 g, 0.15 g, 0.2 g, and 0.25 g.
## 3 HSP-QGA Algorithm Design
### Algorithm Design
#### 3.2.2 Chromosome Decoding  
As \(\left|\alpha\right|^{2}\) and \(\left|\beta\right|^{2}\) tend to 0 or 1, each quantum gene bit will converge to a single state. Thus each quantum gene can eventually tensor to 0 or 1, which can be abstracted into the \"0\" and \"1\" codes of the binary string in the mathematical model. In the decoding process, using this mapping relationship, each quantum gene is decoded as 0 or 1, and each chromosome is decoded into a binary string of length \(m\). By converting the binary string to a real number so that each chromosome represents a real number, i.e., a processor serial number. Finally, a processor scheduling strategy of n length is obtained by fully decoding quantum individuals. According to this decoding method, all individuals in the population are decoded.  
To better describe the problem of chromosome coding and scheduling strategies, we have mapped quantum genetic algorithms and task scheduling, as shown in Table 2. Let us assume that there are 4 processors, numbered from 0 to 3. The number of tasks is five, and the number of chromosomes is also five according to the chromosome coding process. The number of quantum genes per chromosome is \(m\ =\ \left[\log_{2}^{4}\right]=2\). \(\begin{pmatrix}\alpha_{11}&\alpha_{21}\\ \beta_{11}&\beta_{21}\end{pmatrix}\) denotes a chromosome encoded by 1 quantum bit. Based on the criterion of \(\left|\alpha\right|^{2}+\left|\beta\right|^{2}=1\), the initial value of \(\left(\alpha_{i},\beta_{i}\right)^{T}\) can be set to \(\left(\frac{1}{\sqrt{2}},\frac{1}{\sqrt{2}}\right)^{T}\). The bit coding is converted to binary coding according to some rules (e.g., generate a random number in the interval \([0,1]\) and assign \(\alpha\) to 1 if the number is greater than \(\alpha^{2}\)). In a binary string, every two neighboring numbers are converted into real numbers. In the end, two processor scheduling policies can be generated. For example, scheduling policy 1 is to assign tasks 1-5 to processors with serial numbers of 1, 3, 1, 0, 2, respectively. With quantum bit coding, we can also see that two scheduling strategies are generated. Compared to traditional genetic algorithms, this approach increases the diversity of the population.
## 4 Conclusions  
The paper presents a study on the dynamic characteristics of a blade's vibration response relative to a bladed disc by considering the bladed disc's rotation, and an effective method for deciding the steady-state of the blade is proposed. The influences of the mass of the damper, the damper's vibrational stiffness, and the external excitation amplitude are discussed. The following conclusions can be drawn:  
1. The dynamic model and analysis method presented in this paper are effective to study the influence of a bladed disc's rotation on the dynamic characteristics of a turbine blade. The changes of the convective inertial force and Coriolis inertial force during the rotation of the bladed disc have a significant influence on the hysteretic constructive relationship of friction-relative displacement and the characteristics of the system dynamics.
2. When the friction contact surface is not detached, changing the damper mass, the damper vibration stiffness, and the external excitation amplitude, results in only higher harmonics in the system response and friction force, and in the system's response, bifurcation and chaos cannot be observed.
3. With proper parameters, adding a platform damper will make the turbine blade's vibration reduce obviously. When the steady-state response is periodic, the reduction law of the average power of blade vibration and the maximum absolute value of the steady-state response are basically the same. However, reduction laws of the average power of blade vibration and the maximum absolute value of the transient response are different. With some parameters, the reduction effect of the transient response may be negative. Greater normal pressure would be needed to keep the damper working well when the external excitation amplitude increases.
4. In engineering, the vibrational reduction effects of the steady-state response and the transient response should be analyzed comprehensively in the under platform-damper design.  
Figure 16: The influence of external excitation amplitude on the reduction of the maximum absolute value of vibrational response.  
Figure 15: The influence of external excitation amplitude on the vibrational power reduction.  
**Author Contributions:** [PERSON] conceived the paper. [PERSON], [PERSON], and [PERSON] wrote the paper and clarified the key methods and results. [PERSON] helped in the programming and data analysis. [PERSON] edited the manuscript.  
**Funding:** This research was funded by the National Key R&D Program of China (grant number 2016 YFE0125600) and the National Natural Science Foundation of China (grant number 51405452).  
**Acknowledgments:** The authors are grateful to the discussion on compositive motion with Doctor [PERSON].  
**Conflicts of Interest:** The authors declare no conflict of interest.
## 3 Biosynthesis of Aromatic and Isoprenic Precursors of Prenylquinones in Parasitic Protozoa
### Isoprenic Side Chain Biosynthesis
#### 3.2.3 Isoprenic Chains Elongation  
Generalities about Isoprenic Chains Elongation  
Regardless of the isoprenoid biosynthetic pathway, IPP and DMAPP can be transformed to their respective isomers by the action of an IPP isomerase [96]. The isomerization of IPP and DMAPP and subsequent elongation of isoprenic chains seems to occur in most living organisms [96; 118] (Figure 1). The simplest elongation occurs by condensation of the IPP molecule and DMAPP to form geranyl pyrophosphate (GPP) by the enzyme GGP synthase. Subsequently, GPP can be condensed with another IPP molecule to form FPP by the enzyme FPP synthase. If FPP is condensed with IPP once again, geranylgeranyl pyrophosphate (GGPP) is formed, a reaction catalyzed by the enzyme GGPP synthase. This elongation process can continue for the formation of chains of different sizes [119; 120; 121]. For example, chains of nine isoprenic units (solanesyl pyrophosphate) can be formed for UQ-9 biosynthesis.  
Isoprenoid metabolism-based chemotherapeutic strategies against parasitic protozoa include not only the MEP and MVA pathways but also the elongation of isoprene chains. Risedronate and its analogs are compounds that are used in human and veterinary clinics for prevention and treatment of osteoporosis, but in trypanosomatids and apicomplexan parasites, these compounds have been shown to be effective as FPP/GGPP synthase inhibitors and affect the calciosomes [123; 124; 125; 126; 127; 128]. Several terpenes of essential oils, such as nerolidol or famesol, appear to have growth inhibitory activity in different species, including apicomplexan and trypanosomatid parasites [129; 130; 131; 132; 133]. Some authors have suggested that these effects are due to the structural similarity of these compounds to prenyltransferase/synthesize substrates, with which the abovementioned terpenes could compete [128; 129; 130; 131; 132]. Moreover, farnesol is also an MVA pathway inhibitor in some organisms [134].