esa-sceva/satcom-chunk-collection huggingface dataset:
# On Ad Hoc Communication in Industrial Environments
## 5 Examination of the Industrial Ad Hoc Channels
### Route Lifetime  
The route lifetime describes how long a connection between two nodes persists before the ability to transmit data is lost. This is an important parameter in the analysis of applicability for certain network technologies. A low route lifetime would, for example, lead to more route failures and therefore more overhead in a MANET routing protocol. The average route lifetime is equivalent to the previously used parameter \(D_{\varnothing}\).  
Figure 4 shows the probabilities for route lifetimes in the three scenarios. This metric also iterates the same trend as the previous: From static office scenario over static industrial scenario to mobile industrial scenario the route life time decreases. In the static office scenario an average route life time of about 39 s was observed. Interference between nodes or with other signal sources is rare. This route lifetime significantly decreases when the same setup is observed under industrial conditions. The route lifetime further decreases when observing mobile nodes. Two AGVs are within communication range for far longer than 1.21 s (assuming a communication range \(r=20\) m and an AGV speed \(v=1\) m/s; an encounter duration of 20 s follows); therefore, the further decrease in route lifetime cannot be explained by the distance between the AGVs and their communication range. Rather, effects on the primary line-of-sight path or on secondary propagation paths might be the cause of the increased number of disconnections.  
Figure 3: Percentage of unidirectional connections in scenarios.
# Evaluation of Antioxidant and Anticorrosive Activities of _Ceriops_ _tagal_ Plant Extract
## 2 Materials and Methods
### Corrosion Inhibition
#### 2.5.2 Atomic Adsorption Spectrometric (AAS)  
The concentration of Fe\({}^{+}\) ions in corroduct solutions without and with green inhibitors were examined by AAS to provide a clear picture about the formation of protective films on the test specimen. The mild steel coupons of 0.785 cm\({}^{2}\) size were kept incubated in 1 M HCl without and with different concentrations (100, 200, 300, 400, 500, and 600 ppm) of _C. tagal_ extract for 3 h at 303 \(\pm\) 1 K [31]. After incubation, the corroduct solutions of both uninhibited and inhibited samples were read for absorbance in an atomic absorption spectrometer (AAS, Model GB 908, Australia). The percentage inhibition efficiency was calculated using the following equation:  
\[\text{Inhibition efficiency ($\eta$\%)}=\text{B}-\text{A}/\text{B}\times 100 \tag{7}\]  
where B and A are the amount of dissolved iron in the absence (B) and the presence (A) of the inhibitor, respectively.
# Collaborative Channel Perception of UAV Data Link Network Based on Data Fusion
## Appendix A  
```
1:\(\{Rn_{f_{f}}^{j},Rn_{f_{f}},Sn_{f_{f}}^{j},Sn_{f_{f}}\}\), \(\{\xi_{i},z_{i},s_{i},mon_{i_{j}},MTBF_{i}\}\)
2:Output: the channel occupancy statistics (Cos)
```  
```
1:\(\{m_{ij}(\text{H}_{1}),m_{ij}(\text{H}_{2}),m_{ij}(\text{H}_{3}),m_{ij}(\text {H}_{4}),m_{ij}(\text{H}_{5})\}\);// a set of score
2:\(m_{j}=\{m_{j}(\text{H}_{1}),m_{j}(\text{H}_{2}),m_{j}(\text{H}_{3}),m_{j}( \text{H}_{4}),m_{j}(\text{H}_{5})\}\);// the basic probability assignment function
3:\(md_{ij}=\text{sqrt}(\left(m_{i}-\frac{1}{2}\right)\left(m_{j}-\frac{1}{2} \right)\left|((m_{i}-m_{j})^{2})\right)\);// the Euclidean distance
4:\(\mathbf{SM}=(1-md_{ij})_{n\times n}\);// similarity matrix
5:for (\(j=1\) to \(5\)) do
6:\(\quad Crd(m_{j})=\frac{1}{5-\sum\limits_{\begin{subarray}{c}i=1\\ i\
eq j\end{subarray}}^{5}}\left(1-md_{ij}\right)\);// credibility of node data
7:end for
8:\(k_{0},k_{j}\);// the global conflict and the local conflict
9:\(F\left(m_{j}\right)=\left(k_{0}-k_{j}\right)/\left(1-k_{j}\right)\);// falsity of node data
10:\(\lambda_{j}=\exp\left(-I\left(m_{j}\right)/\sum\limits_{k=1}^{n}I\left(m_{k} \right)\right)\);// the relative certainty index
11:\(\text{$Crd^{\prime}\left(m_{j}\right)$, $F^{\prime}\left(m_{j}\right)$;// corrected credibility and falsity}\)
12:for (\(i=1\) to \(5\)) do
13:\(\quad\quad\omega_{j}=\text{nthroot}\left(\prod\limits_{i=1}^{5}Crd^{\prime} (m_{i}),5\right)+\text{nthroot}\left(\prod\limits_{i=1}^{5}[1-F^{\prime}(m_{ i})],5\right)\);// weight of node
14:end for
15:for (\(j=1\) to \(5\)) do
16:\(\quad\quad\alpha_{j}=\omega_{j}/\sum\limits_{k=1}^{N+1}\omega_{k}\);// the normalized weight
17:end for
18:for (\(j=1\) to M) do
19:for (\(i=1\) to M) do
```  
**Algorithm 1** Collaborative channel perception based on data fusion
## 2 Experimental Program and Data Preparation
### Data Statistical Information  
After experimental tests, the data were collected and summarized in Appendix A (Table A1), whereas the statistical information of the dataset is presented in Table 4.  
In this study, input variables considered were coarse aggregates (%), two types of bitumen, namely Bitumen 60/70 and PMB I, and the cellulose fibers contents (%). In this study, the polymer-modified bitumen was selected since it is one of the most common types of modified binders in Vietnam and many other regions [31; 32; 33]. The targets were three Marshall Parameters, i.e., MS, MF and MQ. The histogram of the inputs and outputs are presented in Figures 3 and 4. It is noticed that all the values of inputs and outputs parameters covered a reasonable range, which corresponded to typical characteristics of the SMA mixtures as well as SMA component materials.  
Figure 2: The SMA samples preparation and testing: (**a**) Asphal mixer, (**b**) Marshall Automatic Compaction machine, (**c**) The SMA samples in hot water bath, and (**d**) Automatic Stability Testing machine.  
Figure 4: Histogram of the output parameters considered in this study for: (**a**) Marshall Stability (MS); (**b**) Marshall Flow (MF) and (**c**) Marshall Quotient (MQ).  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Parameters** & **Unit** & **Minimum** & **Maximum** & **Average** & **StD \({}^{*}\)** & **Median** \\ \hline Coarse aggregates & (\%) & 71.17 & 76.1 & 73.82 & 2.05 & 74.2 \\ Bitumen 60/70 & (\%) & 0 & 7.0 & 4.17 & 3.00 & 6.00 \\ PMB I & (\%) & 0 & 7.5 & 2.17 & 3.12 & 0 \\ Cellulose fiber & (\%) & 0 & 0.5 & 0.25 & 0.18 & 0.25 \\ MS & (kN) & 6.4 & 11.32 & 7.99 & 1.02 & 7.85 \\ MF & (mm) & 2.55 & 4.65 & 3.21 & 0.44 & 3.20 \\ MQ & (kN/mm) & 1.38 & 3.45 & 2.54 & 0.44 & 2.65 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Statistical analysis of the inputs and outputs in this study.  
Figure 3: Histogram of the input parameters in this study for: (**a**) coarse aggregates; (**b**) Bitumen 60/70; (**c**) PMB I Bitumen and (**d**) cellulose fibers.
## 2 Background and Related Literature  
In this section, the salient features of existing methods are extensively discussed. There is a lot of literature available for identifying time-series anomalies, which is classified into two categories. The first set of strategies examines each individual time series using univariate models, whereas the second uses several time series as a single entity. Furthermore, current anomaly detection systems may be classified into two paradigms: reconstruction-based and forecasting-based models. This section summarizes major studies on time-series anomaly detection and delves further into these two paradigms.
# Implementing and Testing a U-Space System: Lessons Learnt
## 4 GCS Integration
### Arquimea  
As previously said, Arquimea chose to embed the dialogues with U-space in their GCS instead of using the Web interface. The main reason for this was related to the peculiarities of fixed-wing take-off and landing maneuvers. During take-off, fixed-wing aircraft heavily rely on the wind at the precise moment of the maneuver, making it challenging to plan its trajectory well in advance. Moreover, there exists a transition period after take-off, during which the aircraft reaches the desired altitude and then follows the planned flight path. Predicting this transition accurately is complex. Similarly, during the landing maneuver, there is a transition between the last point of the flight plan and the beginning of the descent orbit. This descent orbit may be performed multiple times to achieve the desired altitude and start the landing phase. The management of these peculiarities was addressed by the GCS software. There was no need or reason to delegate it to the path planner. The GCS would add the necessary maneuvers to the trajectory returned by the Operation Plan Processing service. Therefore, it was more convenient to perform the request process already in the GCS, since these maneuvers would not be displayed in the Web app.  
Regarding the technical aspect of the integration, the processing of the JSON messages was straightforward thanks to the existing libraries for C#, the only problem being the incompatibility between some JSON field names and the variable names permitted in C#, which prevented an automated deserialization.
## 3 Results and Discussion
### Contact Angle Measurements  
The analysis of the water contact angle of the surfaces is an easy method for detecting surface changes at the monolayer level. In previous papers, it has been shown that wetting behavior is influenced by the nature and length of the pendent chain [51], as well as the surface group's concentration [36].  
The values of the water contact angles and profiles of the water drops on the uncoated glass substrate and the glass substrates coated with fluorinated silica materials (samples F1 and F2) are shown in Figure 10. According to this figure, it can be observed that the wetting behavior of coatings depends on the fluorinated silica materials which were deposited onto the glass substrates. Both samples F1 and F2 developed a hydrophobic property (92 \(\pm\) 1.3\({}^{\circ}\), and 110 \(\pm\) 1.2\({}^{\circ}\), respectively) in comparison with uncoated glass substrate (35 \(\pm\) 1.6\({}^{\circ}\)). In the case of fluorinated hybrid coatings, some of the silanol groups on the film surface were replaced by alkyl groups (methyl, hexadecyl), and this phenomenon led to a modification of the surface activity.  
The increase in the water contact angle values can be attributed to the length of the functional group, following the order of MTES \(<\) HDTMES. It has been reported that the coating exhibits a hydrophilic character when the interaction forces between the water and the substrate are almost equal to the cohesive forces of the bulk water. In this case, the water does not drain cleanly from the substrate. The decrease in the contact angle may be due to unstable siloxane groups (Si-O-Si) or the presence of free silanol groups (Si-OH). These groups create polar and reactive surfaces, conferring interaction with water molecules that were physically adsorbed through the hydrogen bonds [52]. In previous reports, it has been demonstrated that the water contact angle increase could be associated with to a large amount of air entrapment between the silica material, forming a composite microstructure of the solid film and the air that reduces the effective contact area of water from the surface [53].  
Figure 10: Values of the water contact angles and profiles of the water drops on the uncoated glass and the fluorinated hybrid coatings (TEOS/MTES/FS (F1) and TEOS/MTES/HDTMES/FS (F2)).
## 4 Applications in Clock Recovery and Fiber Optic Supported Radio Frequency Communications  
In this section, we demonstrate applications of injection locked RTD-PD oscillator devices in microwave photonics systems. The ability to lock to reference RF sources by optical injection locking techniques allows remote synchronization providing a large range of functions including generation, amplification and distribution of RF carriers, clock recovery, carrier recovery, modulation, and frequency synthesis. Optically controlled RTD-based photo-detectors can have interesting applications in the generation of microwave stable low-phase noise signals ranging from wireless communications [17] to high-speed optical communications such as radio-over-fiber networks [20], from clock recovery systems to low-power miniature atomic clocks as time references [16]. In what follows two main applications of RTD-PD oscillators in high-speed optical communication transmission systems are discussed: clock-recovery of Gb/s return-to-zero signals and transmission of modulated signals in wireless/photonics links.  
Figure 6: (**a**) Power spectra of the free-running and locked signals. (**b**) Single side band phase noise measurements.
# Microsseismic Source Location Method and Application Based on NM-PSO Algorithm
###### Abstract
Improved numerical results and convergence speed [33], ImWOA algorithm Added diversity to the solution, avoiding the low solution accuracy [34]. The projected algorithm (mWOAPR) is utilized to segment the COVID-19 chest X-ray images [35]. [PERSON] et al. [36; 37] Adopted different methods to improve the problem of a significant error in the arrival of P-wave and improved the accuracy of the source location. [PERSON] et al. [38] established a velocity model without velocity measurement and inversion. Thanks to the powerful nonlinear operation level of deep learning, intelligent and automatic mine microseismic location has been realized [39; 40]. When the sensors are arranged in benign arrays, the traditional localization method relying on the coefficient matrix can quickly obtain the optimal hypocenter location. The aforementioned least squares method, Geiger algorithm, and NM simplex algorithm are representative of such localization methods. On the contrary, if the sensor layout is a non-benign array, the accuracy of the positioning method relying on the coefficient matrix cannot be effectively guaranteed, and the method is prone to divergence and non-convergence. When the sensors are arranged as non-benign arrays, the swarm intelligence algorithm (global search algorithm) can also find the best microseismic source position and maintain a high positioning accuracy. The usual methods of this kind of algorithm include a Simulated annealing algorithm, PSO algorithm, genetic algorithm, etc. The disadvantage is that the convergence speed is lower than the traditional positioning method. In actual underground geotechnical engineering applications, due to the complex geological conditions, such as fault fracture zones, joints, fissures, etc. [41; 42]. Sensor deployment arrays are not always guaranteed to be benign arrays, and there may be situations where benign arrays cannot be deployed. Therefore, A NM-PSO seismic source localization algorithm combining the NM algorithm and PSO algorithm is proposed based on the Time Difference of Arrival source localization theory. The proposed algorithm uses the global search property of the PSO algorithm to perform a global search for optimization, reduces the size of solution space, and provides optimized initial values for the NM algorithm. Reducing the problem of the NM algorithm is sensitive to the selection of initial values; it uses the fast iteration property of the simplex algorithm to speed up the convergence of the model and prevent the model from falling into local optimum or divergence problems.
## 3 Results and Discussion
### Coliform Bacteria  
Coliforms were analyzed in the wastewater by CFU counting after several weeks of operation in order to examine the system in a mature state. Diluted samples from the vermifilter feed, vermifilter effluent/hydroponic feed, hydroponic effluent, and final holding reservoir, taken in 1-mL aliquots, did not provide useful counts. Based on the analysis of undiluted samples, vermifiltration resulted in a reduction of coliform bacteria by 54%. Elimination of coliforms by vermifiltration has been reported before [18; 21; 28; 52]. Vermifiltration coliforms removal efficiency was reported to increase exponentially with environment temperature, reaching 100% at 34 \({}^{\circ}\)C and 45 to 60% at 20 to 25 \({}^{\circ}\)C [52], which corresponded to the system operation conditions in this work. Coliform removal efficiency should, therefore, be improved by setting and keeping the vermifilter at a higher temperature. The hydroponic treatment, also operating at room temperature, contributed to reverse the initial removal effect, increasing coliform content by 56% relative to the vermifilter effluent; the treated water reservoir showed a further increase by 55% (Figure 3), reaching final counts significantly above the maximum limits for any water use, imposed by Portuguese law (maximum 500 per 100 mL, depending on the intended use) [49]. Presumably, the long hydroponic residence time and the additional storage of the treated water in a reservoir gave the bacterial population a chance to grow. The return of reservoir water to vermifilter feed at 80 to 90% contributed, in turn, to higher feed coliform loads. The observation that using coliform-contaminated wastewaters for hydroponic growth can provide good proliferation conditions and increase coliform contamination of the final effluent is a threat to the goal of reusing vermifiltered wastewater for edible crop production. However, this should be easier to address in hydroponic systems than in soil-based agriculture. Water decontamination by ultraviolet light after vermifiltration might be a solution to this problem.
## 2 Design Principle and Procedure
### Design Procedure  
In order to provide designers with profound insights into our proposal, the design process of the holographic source-integrated metasurface is summarized as follows.  
1. First of all, the required parameters should be decided before the holographic calculation, including operation frequency (\(f\)), size of the aperture (\(D\)), depth-of-field of the non-diffracting beam (\(Z_{\text{max}}\)), the base angle of the equivalent (\(\beta\)), topological charge (\(l\)) and polarization.
2. Afterward, according to the selected parameters, the desired object wave \(\mathbf{P}_{CPBOAM}\) and the reference wave \(\mathbf{H}_{ref}\) were expressed analytically. The former was related to the characteristics of the radiated beam, while the latter was associated with the type and location of the feeding source.
3. In the next part, we calculated two linearly polarized holograms (\(M_{y}\) and \(M_{x}\)) and obtained their phase hologram distribution (\(phase_{y-pol}\) and \(phase_{x-pol}\)).
4. After that, we normalized the holographic phase distribution to the same range and defined the judging threshold (\(\theta_{\text{f}}\)). Following the binary judging criterion, we obtained the slot-type distribution patterns (\(S_{y}\) and \(S_{x}\)) generated by two linearly polarized object waves (\(P_{objy}\) and \(P_{objx}\)).
5. In the end, we superposed the slot-type distribution patterns (\(S_{y}\) and \(S_{x}\)) generated by two linearly polarized object waves to obtain the final slot-type pattern (\(S\)) of the circularly polarized quasi-non-diffractive vortex wave. According to the resulting slot-type pattern, a metasurface with the capability of steering the circularly polarized quasi-non-diffractive vortex wave can be established finally.
# Use of SMAP Soil Moisture and Fitting Methods in Improving GPM Estimation in Near Real Time
## 3 Model and Method
### Fitting Correction Methods
#### 3.3.3 CDF Fitting Correction  
The CDF matching correction method is on the assumption that the precipitation at each grid cell is subject to the probability density function f(x). The gamma function is adopted to characterize the precipitation distribution  
\[\mathrm{f}(\mathrm{x})=\mathrm{P}^{\mathrm{k-1}}\ \frac{\exp\bigl{(}-\frac{ \mathrm{x}}{\mathrm{x}}\bigr{)}}{\Gamma(\mathrm{k})\mathrm{\theta}^{\mathrm{k}}}, \tag{9}\]  
where k and \(\mathrm{\theta}\) are the shape and scale parameters of the gamma distribution respectively, which can be obtained by the maximum likelihood function method. The corrected rainfall is expressed as  
\[\mathrm{P}_{\mathrm{CDF}}(\mathrm{i},\mathrm{t})=\mathrm{F}_{\mathrm{CMPA}}^{-1 }(\mathrm{F}_{\mathrm{O}}(\mathrm{P}_{\mathrm{O}}(\mathrm{i},\mathrm{t}))), \tag{10}\]  
where \(\mathrm{P}_{\mathrm{CDF}}\) refers to the CDF-corrected GPM (or SMP) precipitation, \(\mathrm{P}_{\mathrm{O}}\) is the GPM (or SMP) precipitation, \(\mathrm{F}_{\mathrm{O}}\) is the calibrated CDF of GPM (or SMP) based on the 2015-2016 data, and \(\mathrm{F}_{\mathrm{CMPA}}^{-1}\) represents the inverse process of CDF of CMPA precipitation.
# Analysis of Low Cost Communication Technologies for V2I Applications
## 4 Experimentation
### Results  
After the preliminary test and some of the field tests, there were important results for each technology, which are shown in Table 3.  
Figure 8: Experimental design in Boecillo.  
For a complete comprehension of Table 3, the measured features are explained:  
* Range, distance covered by the module in straight line;
* Latency, time spent in sending messages and receiving the check. It depended on the technology, the physical connections, and the clock speed of the microprocessor. The time between messages depended on the latency. The higher it was, the more time was needed to send the next message.  
On completing the field test, there were data of the operation of the devices and when its operation changed depending on the scenery. The influence of the RSU height, position, car speed, and its operation when there is not direct line of sight will be tested.
## 4 The Concept of BIM
### BIM Level of Development (LOD)  
The Level of Development (LOD) refers to the degree of detail and reliability of the geometric and semantic information in a BIM project. This concept reflects the incremental availability of data throughout the design stages. The LOD plays a critical role in BIM execution plans (BEP) [25], and it is often a contractually binding specification in construction projects [26]. The American Institute of Architects (AIA) introduced the LOD in 2008, defining five levels, ranging from LOD 100 (Conceptual Design) to LOD 500 (As-Built). In 2013, the BIM-Forum working group expanded on the AIA definitions by introducing LOD 350, and it continues to update these specifications annually. Table 1 summarizes the different LOD levels as defined by the BIM-Forum.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Level of Development** & **Description** \\ (LOD) & \\ \hline LOD 100 & Model elements are represented graphically in a generic representation. \\ (Conceptual Design) & \\ \hline LOD 200 & The model elements are represented as a generic object with approximate \\ (Schematic Design) & quantities, location, shape, size, and orientation. \\ \hline LOD 300 & Model elements are precisely modeled with their exact quantities, location, shape, size, and orientation. \\ (Detailed Design) & \\ \hline \hline \end{tabular}
\end{table}
Table 1: BIM Levels of Development [27].
## 2 Methods
### Docker and Docker Compose as Solutions
#### 2.9.2 Benefits  
* **Isolation**: Each Docker container runs its own instance of the operating system and dependencies, preventing conflicts between different components and host environments.
* **Portability**: Docker images can be deployed across any system that supports Docker, ensuring consistent behavior regardless of underlying hardware or software variations.
* **Simplified deployment**: Docker Compose orchestrates multiple containers, allowing the entire JAVIS stack, including Nginx, Django, SQLite, Celery, and Vue.js, to be deployed with a single configuration file. This streamlines the setup process and reduces the potential for configuration errors.