esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results
### Relationship between SIF and MODIS at Regional Scale  
At the regional scale, the relationships between SIF and EVI (SIF-EVI), SIF and FPAR (SIF-FPAR), and SIF and LAI (SIF-LAI) for the three vegetation type zones are shown in Figure 4. Linear, exponential, power, and quadratic models were tried for each scatter plot, and we then selected the best fit one. An F-test was used to test the significance of the regression models. Statistically significant relationships were found between SIF and EVI (R\({}^{2}\) = 0.81, \(p\) < 0.001), SIF and FPAR (R\({}^{2}\) = 0.69, \(p\) < 0.001), and SIF and LAI (R\({}^{2}\) = 0.67, \(p\) < 0.001), indicating that regional scale vegetation canopy greenness can reflect increasing vegetation photosynthetic activity. SIF-EVI has a higher correlation coefficient than SIF-FPAR and SIF-LAI.  
The relationships identified between SIF and EVI, SIF and FPAR, and SIF and LAI for cropland, forest, and grassland were also calculated (Figure 5). The results reveal significant correlations in all three land cover types considered, with R\({}^{2}\) values ranging between 0.71 and 0.88 (\(p\) < 0.001). This indicates that in each land cover type, vegetation greenness and photosynthetic activity are consistently related at a regional scale. The strongest relationship was observed between SIF and EVI in cropland, whilst grassland yielded the strongest SIF-FPAR relationship. The R\({}^{2}\) values calculated for SIF-LAI were similar for cropland, forest, and grassland.  
Figure 3: Multi-year averages of 16 d SIF values for cropland, forest, and grassland ecosystems.  
Figure 4: Relationships of SIF–EVI **(a)**, SIF–FPAR **(b)**, and SIF–LAI **(c)** in the study region, where **means \(p<0.001\).  
Figure 5: Relationships between SIF and EVI, SIF and FPAR, and SIF and LAI for cropland, forest, and grassland areas (\(p<0.001\)).
# On-Board Parameter Optimization for Space-Based Infrared Air Vehicle Detection Based on ADS-B Data
## 2 Methodology
### Spectral Characteristics of Civil Aircraft with Multiple Flight Phases
where \(T_{0}\) is the ambient temperature; \(k\) is the recovery factor; \(\gamma\) is the gas constant; and \(M\) is the flight Mach number. In addition, in order to reduce the fuselage temperature during daytime flight, civil aircraft generally use white paint with a relatively high reflectivity [30]. This makes the solar scattering strong during daytime, which cannot be ignored. Therefore, the total infrared radiant intensity of the airframe can be expressed as  
\[I_{skin}=\varepsilon_{skin}\frac{M(T_{skin},\lambda)}{\pi}A_{skin}+r_{skin} \frac{S_{sol}\cdot\left(\overset{\rightarrow}{N}\cdot\overset{\rightarrow}{S} \right)}{\pi}A_{ref}, \tag{3}\]  
where \(T_{skin}\) is the temperature of the airframe, \(\varepsilon_{skin}\) and \(r_{skin}\) are the emissivity and reflectivity of the airframe, respectively, \(M(T_{skin},\lambda)\) is the airframe spectral radiant emittance, \(A_{skin}\) is the projected area considering the detection angle and occlusion, \(S_{sol}\cdot\left(\overset{\rightarrow}{N}\cdot\overset{\rightarrow}{S}\right)\) is the effective solar irradiance on the airframe and \(A_{ref}\) is the effective area of the aircraft skin reflecting solar radiation. In certain spectral bands and applications, the impact of sky and earth radiation must be considered; we ignore these terms in this paper.
# Optical Design for Laser Diode Scanner Headlamp with
###### Abstract
The light emitted from the source is deflected by a micromirror such that it can be illuminated in the desired direction. In this case, it is desirable to collimate the light emitted from the source such that a limited size scanning mirror can be used while increasing efficiency. As an LED has a wide emission pattern, it is difficult to collimate while maintaining high efficiency. Therefore, it is desirable to use laser diode light as a light source to collimate light maximally and then send it to the scanning mirror. In addition, to construct a pixelated system with a small number of light sources, it is advantageous to use a laser diode source with a higher light efficiency than LEDs, as shown in Figure 1.  
Figure 1: Schematic diagram of pixelated system using a single laser diode source. Generally, three methods of scanning using a mirror exist. The first is to create a Lissajous pattern while both axes operate in the resonance mode, as shown in Figure 2a. When forming the Lissajous pattern, the scanning light is decelerated at the edge of the illumination area because of the sinusoidal path of the resonance mode; therefore, the illuminance at the center is relatively low compared with that at the edge. In vehicle headlamps, the light intensity in the center should generally be the largest. Therefore, a light source with an extremely high intensity is required to drive both axes at high speed and at a resonance frequency. Therefore, if the beam is formed in the Lissajous pattern, the light at the edge will have a higher light distribution than the center area, which is inefficient for realizing the vehicle headlamp. In the second method, as shown in Figure 2b, one axis operates in the resonant mode and the other axis operates in the quasistatic mode. This method can output light relatively uniformly in the short axis, which can then be driven at a relatively low speed; however, in the long axis, the illuminance in the center is reduced for the same reason as discussed for the Lissajous pattern. In the third method, both axes operate in the static mode. Although the illuminance can be increased in all areas, the frame rate is extremely low, rendering it unsuitable for forming complex patterns when driving at high speeds. Herein, we propose a new laser diode scanning optical scanning system that can be used in a pixelated system to build an ADB headlamp. The proposed optical system design involves adding a simple optical prism to improve the amount of light in the center (which is lower than that at the edge area) that inevitably occurs in mirror scanning in the conventional resonance mode. By applying an optical scanner designed in this manner, an optical scanner applicable to vehicle headlamps that can increase the amount of light in the center compared with that at the edge can be implemented without using a complicated control method.
## 5 Understanding Decentralised Identity Systems
### EverID
#### 5.8.2 Limitations  
EverID also functions as a self-sovereign identity (SSI) and value transfer system, allowing users to control how their data are shared. However, this is not fully realised, as users are required to disclose all their information when verifying a claim, which does not adhere to the principle of data minimization [71]. Additionally, since EverID operates on a permissioned Ethereum blockchain, access is restricted to approved participants, introducing a level of centralisation. As the number of transactions and users increases, it could lead to higher operational costs, slower transaction speeds, and could negatively affect user experience and the overall efficiency of the EverID ecosystem.
# New Landslide Disaster Monitoring System: Case Study of Pingding Village
## 3 Results  
### Monitoring Warning Systems  
The data of different devices can be displayed in the following ways: Image data displays, cover real-time image displays, and historical image displays, as demonstrated by Figure 6.  
Figure 5: Arrangement of the devices presented in Pingding. The monitoring station is equipped with a rain gauge, a CCD camcorder, a high-pressure tiltmeter, a remote camcorder, a geophone, and slope circles (dual direction).  
Two types of real-time image displays are available: Single-station displays and loop displays of data from all of the observation stations. Historical image displays allow users to browse the CCD images of certain chosen time periods through the single-station display mode. The slope displacement condition is shown through the displays and analyses regarding the space transformation condition of the retractable meters (tensile strain meters) and the GPS slope land deformation monitoring systems. Users are allowed to access the displacement condition through direct clicks on the devices shown in the device arrangement figure, which is a vigilance data reference provided for involved staff, as displayed in Figure 7. There are four groups of retractable meters, while the data displays show the conditions of the devices using red, yellow, and green lights, as per the display mode of the device set up procedures. When the displacement quantities of the retractable meters exceed the set threshold of the vigilance values, the system will switch the light to red or yellow to remind the responsible personnel of the meters' current condition. The GPS slope land deformation monitoring systems also display the devices' condition through red, yellow, and green lights, and the lights are switched to red or yellow as a reminder for personnel responsible for the current GPS conditions, as shown in Figure 8. In both situations, users are also permitted to click on the red or yellow light icons to inquire about the detailed displacement condition of a particular piece of equipment. The slop circle data displays analyze and display data, focusing on the condition of the angle changes of the slop circle. Users are allowed to access the displacement condition through direct clicks on the devices shown in the device arrangement figure, which is a vigilance data reference provided for relevant staff, as displayed in Figure 9. The real-time monitoring data of all of the devices and the arrangement figures of the relevant devices are shown in Figure 10.
# Disturbance Observer-Based Anti-Shock Controller for Laser Beam Steering Systems
## 2 FSM Control System
### Tip-Tilt Controller of FSM Control System  
PI controllers are commonly used in real control systems for the tip-tilt control of FSM control systems. The tip-tilt controller is designed to achieve the designed gain margin, phase margin, crossover frequency, and loop gain. Although it is feasible to obtain a wider crossover frequency, the crossover frequency is limited by the sampling frequency of the DSP, feedback sensor signal, and other components. The open-loop transfer function of the designed PI controller for FSM control systems is illustrated in Figure 3, where the PI controller, crossover frequency, gain margin, phase margin, and loop gain are 91.1 Hz, 11.8 dB, 68.7\({}^{\circ}\), and >30 dB, respectively. Moreover, the disturbance-rejection performance of the designed PI controller for FSM control systems is depicted in Figure 4. The transfer function of the PI controller is expressed as follows [35]:  
\[C(s)=K_{P}+\frac{K_{I}}{s}=0.5+\frac{900}{s} \tag{3}\]  
where \(K_{P}\) and \(K_{I}\) are the proportional and integral gains, respectively, and their values are 0.5 and 900, as determined using Equation (3).  
Figure 2: (**a**) FSM control system; (**b**) tip-tilt actuating platform (PI Ceramic GmbH); and (**c**) Scalexio AutoBox (dSPACE).
###### Abstract  
In this paper, we optimize the search and rescue (SAR) in disaster relief through agent-based simulation. We simulate rescue teams' search behaviors with the improved Truncated Levy walks. Then we propose a cooperative rescue plan based on a distributed auction mechanism, and illustrate it with the case of landslide disaster relief. The simulation is conducted in three scenarios, including \"fatal\", \"serious\" and \"normal\". Compared with the non-cooperative rescue plan, the proposed rescue plan in this paper would increase victims' relative survival probability by 7-15%, increase the ratio of survivors getting rescued by 5.3-12.9%, and decrease the average elapsed time for one site getting rescued by 16.6-21.6%. The robustness analysis shows that search radius can affect the rescue efficiency significantly, while the scope of cooperation cannot. The sensitivity analysis shows that the two parameters, the time limit for completing rescue operations in one buried site and the maximum turning angle for next step, both have a great influence on rescue efficiency, and there exists optimal value for both of them in view of rescue efficiency.  
disaster relief; simulation optimization; Truncated Levy walks; distributed auction mechanism; cooperative rescue +
Footnote †: journal:
# Spitzer Resurrector Mission: Advantages for Space Weather Research and Operations
## 3 Mission Design
### Programmatics
#### 3.5.5 Public/Private Partnership  
The currently funded Phase-I of the Spitzer-Resurrector concept has enabled rapid collaboration between space industry stakeholders. The mission as designed achieves advances in space weather experimentation and warning, on-orbit servicing in deep space, planetary defense, and astronomy. This success in leveraging the unique opportunities provided by the mission location can be attributed to mission leadership by a private company, responding to defined requirements and desires of public organizations such as the USSF, NASA, NOAA, and SAO (the Smithsonian Astrophysical Observatory, a partner in the Center for Astrophysics | Harvard and Smithsonian). Rather than any individual public organization proposing and developing a mission in isolation, the private-led effort can move quickly in coordinating stakeholders and find compromises to de-risk future standalone missions. The SRM team already has begun planning for making at least some of the data public and enabling some level of participation by outside experts. Public education and outreach and DEI are important components of the mission.
## 5 Analysis and Results
### Flexibility in the Algorithm  
As it can be seen in previous sections, this algorithm is flexible and can be changed according to IoT scenario requirements. We have discussed that the integral multiplier (\(m\)) can be increased to maximize security in terms of randomness, and validating nodes (\(v\)) can also use different numbers according to the number of validations per the second  
Figure 8: Total time for validation and verification per block.  
Figure 7: Probability of validating nodes.  
requirement. The value of \(N\),\(m\), and \(v\) can be selected according to Equation (1) in the previous section. We choose to select integral multiplier \(m\) to increase randomness or validate nodes \(v\) according to block generation time and verification speed.
## 4 Experiments
### Experiments on UCI Datasets  
To test the performance of SNNISC further, eight real-word datasets are adopted from UCI datasets about classification and clustering [21; 22; 23; 24; 25; 26; 27; 28; 29], and the results are shown in Table 4. From the boldface in the Table 4, we observe that the clustering performance of SNNISC is superior to SSC and SNNSC on four datasets in addition to \"Breast Tissue\" and \"Data Bank\". In particular, for the dataset \"Iris\", one cluster is linearly separable from the other two nonlinearly clusters, which is challenging for clustering algorithms. Although the ARI value of SSC and SNNSC can reach to about 83%, SNNISC can achieve 92%. On dataset \"Seeds\", SNNISC, SNNSC and SSC get the same ARI value (71%).  
On dataset \"Glass\", the ARI value of SNNISC (24%) is less than SSC (27%), but better than SNNSC (23%). Meanwhile, it can be found that SNNISC is more stable, which is just less than the best result between 0.2%-0.3%.Therefore, we conclude that the SNNISC can improve the performance of the spectral clustering algorithm.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Datasets**} & \multicolumn{3}{c}{**Spectral Clustering Algorithm**} \\ \cline{2-4}  & **SSC** & **SNNSC** & **SNNISC** \\ \hline Iris & 0.82 & 0.83 & **0.92** \\ Ionosphere & 0.22 & 0.22 & **0.23** \\ Breast Tissue & 0.20 & **0.22** & 0.18 \\ Banknote & 0.29 & **0.58** & 0.56 \\ Seeds & **0.71** & **0.71** & **0.71** \\ Fertility & 0.11 & 0.11 & **0.12** \\ Libras & 0.37 & 0.37 & **0.38** \\ Glass & **0.27** & 0.23 & 0.24 \\ \hline \hline \end{tabular}
\end{table}
Table 4: The results of ARI on the UCI Machine Learning Repository.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Datasets**} & \multicolumn{3}{c}{**Spectral Clustering Algorithm**} \\ \cline{2-4}  & **SSC** & **SNNSC** & **SNNISC** \\ \hline Flame & 0.95 & **0.97** & **0.97** \\ Jain & **1** & **1** & **1** \\ Spiral & **1** & **1** & **1** \\ Compound & 0.54 & 0.54 & **0.54** \\ Aggregations & 0.97 & **0.98** & 0.97 \\ R15 & **0.99** & **0.99** & **0.99** \\ \hline \hline \end{tabular}
\end{table}
Table 3: The results of adjusted Rand index (ARI) on synthetic datasets. SSC, self-tuning spectral clustering; SNNSC, spectral clustering based on shared nearest neighbors, SNNISC, the adaptive spectral clustering algorithm based on the importance of shared nearest neighbors.
# Robust Backstepping Control Applied to UAVs for Pest Recognition in Maize Crops
## 4 Control Strategy Applied to the Quadrotor
### Controller for Subsystem \(y-\phi\)  
The translational and rotational dynamics experienced by the flying robot along the \(y\)-axis and the roll angle \(\phi\) respectively are represented by  
\[ \begin{array}{l}\ddot{y}=\frac{u_{s}}{\eta}\cos\theta\sin\phi\\ \ddot{\phi}=\phi\psi c_{5}+c_{6}\tau_{\phi}+\delta(t,\vartheta),\end{array}  \tag{28}\]  
where \(c_{5}=\frac{L_{y}-L_{z}}{L_{x}}\), \(c_{6}=\frac{l}{L_{z}}\). Defining the variables \(x_{9}=y\), \(x_{10}=\dot{y}\), \(x_{11}=\dot{\phi}\), \(x_{12}=\dot{\phi}\), the state space representation is given by  
\[ \begin{array}{l}x_{9}=x_{10}\\ \dot{x_{10}}=\frac{\cos x_{7}}{m}\sin x_{11}u_{s}\\ \dot{x_{11}}=x_{12}\\ \dot{x_{12}}=\dot{\theta}\dot{y}c_{5}+c_{6}\tau_{\phi}+\delta(t,\vartheta). \end{array}  \tag{29}\]  
Considering the first two equations of (29), the virtual input  
\[u_{y}=\sin x_{11}=\frac{m}{u_{s}\cos x_{7}}u_{1}, \tag{30}\]  
and defining \(x_{10}=\mu(x_{9})=-\alpha_{1}x_{9}\), for \(\alpha_{1}>0\); the subsystem is rewritten as \(x_{9}=-\alpha_{1}x_{9}\) and \(x_{10}=u_{1}\). The Lyapunov function is \(V_{1}(x_{9})=\frac{1}{2}x_{9}^{2}\), and according to the classic backstepping methodology, the input \(u_{1}=-(k_{1}\alpha_{1}+1)x_{9}-(k_{1}+\alpha_{1})x_{10}\) is substituted into Equation (30), which yields  
\[u_{y}=\frac{m}{u_{s}\cos x_{7}}[-b_{1}x_{9}-b_{2}x_{10}], \tag{31}\]  
where \(b_{1}=k_{1}\alpha_{1}+1\), \(b_{2}=k_{1}+\alpha_{1}\); substituting (13) into (31)  
\[u_{y}=\frac{\cos x_{11}}{p}(-b_{1}x_{9}-b_{2}x_{10}).\]  
In the next step, the third equation of the state space representation (29) is added, and the subsystem is rewritten as in [11], with \(\vartheta=(x_{9},x_{10})^{T}\), and \(\zeta=x_{11}\), as follows:  
\[ \begin{array}{l}\left[\begin{matrix}\dot{x}_{9}\\ \dot{x}_{10}\end{matrix}\right]=\begin{bmatrix}x_{10}\\ 0\end{bmatrix}+\begin{bmatrix}0\\ \frac{p}{\cos x_{11}}\end{bmatrix}\sin x_{11}\\ \dot{x}_{11}=x_{12}=u_{y2}.\end{array}  \tag{32}\]  
Following a similar procedure applied to the previous subsystems, with \(V_{2}(x_{9},x_{10})=\frac{1}{2}x_{9}^{2}+\frac{\beta_{2}}{2}(x_{10}+\alpha_{1 }x_{9})^{2}\), and \(\mu_{1}=\frac{\cos x_{11}}{p}(-b_{1}x_{9}-b_{2}x_{10})\), a control is obtained as the given in the Equation (24), and it has the following structure:  
\[u_{y2}=-\Big{[}\frac{k_{2}b_{1}}{p}+\frac{\beta_{2}u_{1}p}{\cos^{2}x_{11}} \Big{]}x_{9}-\Big{[}\frac{b_{1}+k_{2}b_{2}}{p}+\frac{\beta_{2}p}{\cos^{2}x_{1 1}}\Big{]}x_{10}-(b_{2}+k_{2})\tan x_{11}. \tag{33}\]  
In the last step, subsystem (29) is fully considered, with \(\vartheta=(x_{9},x_{10},x_{11})^{T}\), \(\zeta=x_{12}\), and defining  
\[\tau_{\phi}=\frac{1}{c_{6}}\big{[}-\dot{\theta}\dot{y}c_{5}+\tau_{1}\big{]}, \tag{34}\]  
it can be rewritten as follows:  
\[ \begin{array}{l}\left[\begin{matrix}\dot{x}_{9}\\ \dot{x}_{10}\\ \dot{x}_{11}\end{matrix}\right]=\begin{bmatrix}x_{10}\\ \frac{p\sin x_{11}}{\cos x_{11}}\\ 0\end{bmatrix}+\begin{bmatrix}0\\ 0\\ 1\end{bmatrix}x_{12}\\ \dot{x}_{12}=\tau_{1}+\delta(t,\vartheta),\end{array}
# Name-Based Security for Information-Centric Networking Architectures
## 3 System Design
### Name Versioning  
Content names are used in our system as public keys which are associated with a secret key. As in any crypto system, a secret key may be breached, hence the corresponding public key has to be modified (we discuss key revocation in more detail in Section 5.3). In order to enable content name modification, we consider the name \"versioning\". A name version is a simple number appended to a content name when necessary. For instance, and as we discuss in more detail in the following section, when a user requests a content item by its name, a network node that hosts this item may reply indicating in its response the version of the name it hosts, e.g., a user may request 'User A/Videos/Graduation\", and a network node may reply with \"User A/Videos/Graduation:1\". In that case, the latter name will be used as the public key in all subsequent cryptographic operations. A content owner may include in the corresponding DID document all deprecated version numbers (akin to a key revocation list).  
Similar to this concept, there are scenarios where ephemeral names are required (e.g., a network entity may be authorized to host a content name for limited time). In these cases, a timestamp can be appended to a content name. The semantics of this timestamp are that \"this name and its corresponding secret key can be used up until the specified timestamp\".
# A Self-Powered UHF Passive Tag for Biomedical Temperature Monitoring
## 3 Design Methodology, Layout and Circuit Simulation
### Design Methodology  
Figure 11 presents the bottom-up design flow used to implement the proposed battery-free temperature sensor prototype which is organized as follows. All circuits are grouped in two main domains, a low-frequency section and a high-frequency section. Each domain includes three columns, where the center column points out the circuit to be designed, the left column indicates the required variables to design the aforementioned circuit, and the right column maps a new set of variables that can be used by further circuits.  
Based on Figure 11, the low-frequency section is firstly designed to determine the total amount of required energy to power the passive tag. It starts with the voltage/current reference circuit and ends with the LDO Regulator circuit. After that, the high-frequency section is outlined to provide such required energy. It starts with the design of the Differential Rectifier circuit and ends with the ASK backscatter modulator.