esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Conclusions  
In this paper, a new hybrid DC-DC converter based on Mahafzah and Zeta converters was proposed. The proposed hybrid converter is made up of a single controlled switch, several synchronized output voltages, two diodes, three inductors, and two coupling capacitors. In comparison to the Zeta and Mahafzah topologies, the novel converter is able to double the voltage gain, yielding a higher voltage gain at a lower duty cycle. This benefit can decrease the voltage stress across the output diodes and semiconductor switches. The paper presents an extensive discussion about the hybrid converter's operating concept. Additionally, the duty cycle was determined. The proposed hybrid converter's employment in two distinct applications was presented in the study. The new converter's first application  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Component** & **Zeta Converter** & **Mahafzah Converter** & **Proposed Converter** \\ \hline Number of switches & \(1\) & \(1\) & \(1\) \\ Number of diodes & \(1\) & \(1\) & \(2\) \\ Number of capacitors & \(1\) & \(1\) & \(2\) \\ Number of inductors & \(2\) & \(2\) & \(3\) \\ Output low pass filter & \(1\) & \(1\) & \(2\) \\ \hline \hline \end{tabular}
\end{table}
Table 4: Component comparison.  
Figure 26: THD of the grid current.  
was as a DC-DC converter in a system for renewable energy. The second was using the new converter as an adaptor (AC-DC converter) for electric vehicles. A simulation at 25 kW, 200 V, and 130 A was performed using MATLAB/SIMULINK to demonstrate the efficacy of the suggested hybrid converter. The outcomes demonstrated the new converter's capacity to support two separate loads with opposing energy flows. In the case of the second application, the analysis of the total harmonic distortion (THD) for the grid current was also provided. When using the new hybrid converter topology, a 21.11% THD of the grid current is attained.  
Conceptualization, K.A.M. methodology, K.A.M. and M.A.O.; software, K.A.M.; validation, K.A.M., M.A.O., A.M., E.R.S. and G.Z.; formal analysis, K.A.M.; investigation, K.A.M. and M.A.O.; writing--original draft preparation, K.A.M., M.A.O. and A.M.; writing--review and editing, E.R.S. and G.Z.; visualization, K.A.M., M.A.O., A.M. and E.R.S.; supervision, E.R.S. All authors have read and agreed to the published version of the manuscript. This research received no external funding. Data Availability Statement Data available on request due to restrictions. The data presented in this study on request from the corresponding author due to the privacy reasons. The authors declare no conflicts of interest.
###### Abstract  
Zirconia (ZrO\({}_{2}\))-based flame retardant coatings were synthesized through the process of grinding, mixing, and curing. The flame retardant coatings reinforced with zirconia nanoparticles (ZrO\({}_{2}\) NPs) were prepared at four different formulation levels marked by F0 (without adding ZrO\({}_{2}\) NPs), F1 (1% _w/w_ ZrO\({}_{2}\) NPs), F2 (2% _w/w_ ZrO\({}_{2}\) NPs), and F3 (3% _w/w_ ZrO\({}_{2}\) NPs) in combination with epoxy resin, ammonium polyphosphate, boric acid, chitosan, and melamine. The prepared formulated coatings were characterized by flammability tests, combustion tests, and thermogravimetric analysis. Finally, char residues were examined with scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS). The peak heat release rate (PHRR) of the controlled sample filled with functionalized ZrO\({}_{2}\) NPs was observed to decrease dramatically with increasing functionalized ZrO\({}_{2}\) NPs loadings. There was an increase in the limit of oxygen index (LOI) value with the increase in the weight percentage of ZrO\({}_{2}\) NPs. The UL-94V data clearly revealed a V-1 rating for the F0 sample; however, with the addition of ZrO\({}_{2}\) NPs, the samples showed enhanced properties with a V-0 rating. Thermal gravimetric analysis (TGA) results revealed that addition of ZrO\({}_{2}\) NPs Improved composite coating thermal stability at 800 \({}^{\circ}\)C by forming high residual char. The results obtained here reveal that the addition of ZrO\({}_{2}\) NPs in the formulated coatings has shown the excellent impact as flame retardant coatings.  
Keywords:ZrO\({}_{2}\) NPs; intumescent flame retardant coatings; SEM; XRD; TGA +
Footnote †: journal: Applied
## 1 Introduction
### Influence of the Perforation Parameters
#### 2.2.1 Perforation Depth and Shot Density  
As shown in Figure 4, the productivity of perforated wells increases with the perforation depth. When the perforation hole does not penetrate the contaminated zone, the productivity ratio increases linearly with the perforation depth, showing a stable growth rate. When the perforation hole just penetrates the contaminated zone, the productivity ratio increases significantly. However, when the perforation hole extends beyond the contaminated zone by approximately 50 mm, the growth rate of the productivity ratio gradually decreases. Furthermore, the productivity ratio increases with shot density, but the growth rate also decreases gradually. Particularly, when the shot density exceeds 24 holes/m, the influence of increasing shot density on enhancing the productivity ratio becomes less significant.
###### Abstract  
Taiwan's provincial highways span approximately 5000 km and are crucial for connecting cities and towns. As pavement deteriorates over time and maintenance funds are limited, efficient pavement inspection and maintenance decision-making are challenging. Traditional inspections rely on manual visual assessments, consuming significant human resources and time without providing quantitative results. This study addresses current maintenance practices by introducing automated pavement damage detection technology to replace manual surveys. This technology significantly improves inspection efficiency and reduces costs. For example, traditional methods inspect 1 km per day, while automated survey vehicles cover 4 km per day, increasing efficiency fourfold. Additionally, automated surveys reduce inspection costs per kilometer by about 1.7 times, lowering long-term operational costs. Inspection results include the crack rate, rut depth, and roughness (IRI). Using K-means clustering analysis, maintenance thresholds for these indicators are established for decision-making. This method is applied to real cases and validated against actual maintenance decisions, showing that the introduced detection technology efficiently and objectively guides maintenance decisions and meets the needs of maintenance units. Finally, the inspection results are integrated into a pavement management platform, allowing direct maintenance decision-making and significantly enhancing management efficiency.  
automated pavement damage detection technology; K-means clustering analysis; maintenance decision-making; pavement management platform +
Footnote †: journal:  
involve extensive post-processing, further increasing the time and labor costs. Socially, inspection personnel face prolonged exposure to traffic risks. The reliance on significant human resources and the low efficiency of traditional inspections impact overall decision-making, potentially delaying maintenance plans. Environmentally, traditional methods require substantial paper for data recording and analysis, burdening the environment. Therefore, advanced technologies are necessary to improve the inspection efficiency and effectiveness, reduce costs, minimize environmental impact, and enhance worker safety and efficiency [1; 2].
# Variable Guide Vane Scheduling Method Based on the Kinematic Model and Dual Schedule Curves
## 2 Mechanical Structure of the VGVS  
### Component of the Link Mechanisms  
The axial compressor to be tested consisted of three VGV stages: the VIGV, VGV1 (first-stage variable guide vane), and VGV2 (second-stage variable guide vane), as shown in Figure 1. Three-stage VGVs are connected to the each unison rings through lever arms, and the lever arms and vanes rotate, while the unison ring rotates about the center of the engine. In this research, enough space between the compressor and the hydraulic actuators was obtained by using long vertical links for easy installation of sensors and other components during the development phase of the engine. The unison rings are manipulated by vertical links of the link mechanisms, and extension/compression of the hydraulic actuators induce rotation of bell cranks and vertical movement of the vertical links. Due to using a common bell crank, the rotational motions of the unison rings of three VGV stages are coupled each other, and each motion can be characterized by lengths of their links.
## 5 Calibration of STMD Using Numerical Optimization  
The control force of the sub-optimal STMD, as previously discussed, lacks adjustments to mitigate the effects of force clipping. In this section, an optimized STMD featuring necessary modifications to its control force is presented. These modifications are aimed at compensating for the effects of clipping to the extent possible, thereby improving the calibration and overall performance of the STMD.  
A modified semi-active control force with two incorporated correction factors is subsequently introduced, designed to scale the control force before clipping occurs. The numerical optimization procedure used to calibrate these correction factors are then outlined. Finally, the optimization results as well as an analysis of the optimized STMD at its performance limit are presented.
## 1 Introduction
First, convolution kernels of different scales are used to capture image features and data from different receptive fields are fused to capture features that reduce the computational complexity when combining semantic information [76; 77] from a previous level. Second, a multiscale graph convolution network (MSGCN) module serves as a transitional module between the encoder and decoder. The MSGCN combines the features of the encoding module with its own features to better represent edge and multiscale features [78]. Third, the skip connection is replaced by local attention (LA) [79] that focuses on salient features, thereby reducing the use of redundant information. Fourth, fusion of the decoding layers ensures consideration of both high- and low-level feature information, and improves the attribute decision-making capacity for boundary cells [80]. The main goals of this study are to compare the novel MSG-GCN with other state-of-the-art (SOTA) methods, investigate the specific areas and digital number (DN) of correctly and misclassified forest types, compare U-shaped deep learning models (such as U-Net and U-Net++) and the classical RF machine learning method, and map and classify entire forest areas, as well as determine the spatial distribution of misclassified forest types.
## 3 Key Technologies and Methodologies
### Autonomous Artificial Agent  
A software agent is a computer system situated in a specific environment; that is capable of autonomous actions in this environment in order to meet its design objective [18]. An agent is responsive, proactive and social. Responsive means the agent can perceive its environment and respond in a timely fashion to the changes occurring in it. Proactive means the agent is able to exhibit opportunistic, goal directed behaviour and take initiative. Social means the agent can interact with other artificial agents or humans within its environment in order to solve a problem. An agent is a computing machine which is given a specific problem to solve. Therefore, it chooses certain set of actions and formulate the proper plans to accomplish the assigned task. The set of actions which are available to be chosen by the agent are called a behaviour. The agent's behaviours are mainly created by the agent programmer. An agent can formulate one or more behaviour to reach its target. The selection of an execution behaviour among others would be based on a certain criteria which has been defined by the agent programmer. Building an execution plan is highly depending on the information which the agent infers from its environment including the other agents. An MAS is a collective system composed of a group of artificial agents, teaming together in a flexible distributed topology, to solve a problem beyond the capabilities of a single agent [19].  
JADE is a distributed MAS middleware framework [20]. JADE applies the reactive agent architecture which complies with the Foundation for Intelligent Physical Agent (FIPA) specifications,  
Figure 1: (a) ADACOR (ADAptive holonic COntrol aRchitecture) Model; (b) Holon Generic Structure.  
and provides a graphical interface to deploy and debug a MAS [16]. FIPA is an IEEE Computer Society standards organization that promotes agent-based technology and the interoperability of its standards with other technologies [21]. JADE agents use FIPA-Agent Communication Language (FIPA-ACL) [22], to exchange messages either inside its own platform or with another platform in a distributed MAS as shown in Figure 2. Each JADE instance is an independent thread contains a set of containers. A container is a group of JADE agents run under the same JADE runtime instance. Every platform must contain a main container. A main container contains two necessary agents which are: an Agent Management System (AMS) and a Directory Facilitator (DF). AMS provides a unique agent ID (AID) for every agent under its platform, to be used as an agent communication address. While the DF announces the services every agent can offer under its platform, in order to facilitate agent service exchange, so that each agent can obtain its specific goal [23; 24].
## 2 Implementation of Active Localization: Signal Model, Processing, and Feasibility Test
### Configuration for the Simulations and Experiments  
This section describes the configuration of the simulations and experiments. The configuration shown in Figure 7 was applied to the conceptual verification in an anechoic chamber described in Section 2.4, the analysis of operating conditions described in Section 3, and the experimental verification of the proposed method in a classroom described in Section 4.  
In Figure 7, A, B, C, and D denote the positions of a silent intruder. Two types of intruders were used in the experiments in an anechoic chamber and a classroom. The first was a PVC pipe 0.3 m in diameter. The second was a person.  
The reasons for using two types of intruders were as follows. The PVC pipe was used to identify trends in the localization performance of the proposed active localization method. In other words, using the circular PVC pipe, the reflection sound was uniformly generated even when the sound source was incident at any angle. Therefore, the PVC pipe was used to minimize the change in the absorption ratio of the intruder. The analysis using a PVC pipe was compared with the experimental results of human intrusion and was the background used to simulate the person as a circular boundary.  
Figure 6: Gaussian-modulated sinusoidal pulse: (**a**) in the time domain; (**b**) in the frequency domain.  
Each superscript on the characters A, B, C, and D of the intruder shows the distance between the active localization system and the intruder position, and each subscript shows the counterclockwise angle between the microphone array and the intruder. The active localization system consisted of a loudspeaker, microphone array, and controller. The positions of the silent intruder were represented by the distance and angle, and the positions of the silent intruder were determined to be the event scenarios close to the wall (positions A and D) or the center of the active localization system (positions B and C).  
The size of the control area in the security zone was 2 m \(\times\) 3 m. The microphones used in the experiment were seven-array microphones. The excitation signal in the simulations and experiments was a Gaussian-modulated sinusoidal pulse with a 1 kHz center frequency (Equation (10)) and the spacing between the microphones was configured to be the same as the Nyquist spacing (\(\lambda/2\)), which corresponded to a center frequency of 1 kHz. This was because when designing the beamformer of the single frequency, the Nyquist spacing had the maximum array gain and directivity [37].
## 2 Experimental Data and Study Areas  
Urban scenes in different regions have different appearances related to variation in cultural, social, and economic development patterns. We selected two sites with different layouts: Toronto, Canada, and Beijing, China. Both sites reflect complex urban scenes, including buildings at different heights, and different seasons. To verify the adaptability of the proposed method, the experimental data was collected from Google Earth. The details of the experimental data are shown in Table 1.  
Table 1 shows basic information about the imagery for the cities of Toronto and Beijing. The images were obtained from different scenes at different resolutions to test the robustness of our proposed approach. The acquisition time of the data from Google Earth is accurate to one day. As the images in the experiments reflect different sizes, we resampled them and arranged them side by side in Figure 1.  
Figure 1a shows the urban scene in Toronto in summer. Most of the tall buildings lie from the center to the right of the image, while the residential areas are located in the center-left of the image. The vegetation is spread over the entire image, as seen in Figure 1a. Figure 1b shows Beijing in winter. High-rise buildings lie along the street and in the center. The vegetation is very limited in the scene because of the season and location.
## 3 Results and Discussion
### Total Amino Acids in Tea
According to the authors of other studies, determination of amino acids in water solutions using the HPLC technique may result in numerous difficulties, most of all due to pure linearity, low recovery rates, and high limits of detection and quantification [35]. Due to the lack of a suitable chromophore, it was necessary to label the amino acids using a labelling reagent such as dabsyl chloride, \(o\)-phthalaldehyde (OPA), and phenylisothiocyanate. Such a situation involves precolumn or postcolumn derivatization and detection using a fluorescence or diode array detector (DAD). However, clear chromatograms are very difficult to obtain during analysis of the composition of free amino acids in tea infusions [15; 36]. The internal high-temperature reactor used in the studies conducted by the authors of this work with a coiled capillary for the colour reaction of the amino acid-ninhydrin complex coupled with high temperature postcolumn derivatization of ninhydrin allowed free amino acids to be precisely determined even in the case of low concentrations (sykam.com). [PERSON] et al. [37] additionally applied the solid phase extraction (SPE) analytical technique in order to increase the precision of amino acid determination in green tea, black tea, and oolong tea infusions. As a result, they indicated the highest content of free amino acids in green tea infusions and an approx. 40% lower concentration in the case of black tea infusions in comparison with green tea infusions, which is compliant with the results obtained in this work. According to [PERSON] et al. [28], green tea is a rich source of numerous amino acids important for the human body, such as glutamic acid, aspartic acid, and phenylalanine, and their content significantly exceeds the content of the amino acids in fermented tea. The authors of these studies also draw attention to the presence of non-protein GABA amino acids which together with theanine can be considered to determine the taste and quality characteristics for these types of tea. Therefore, it is necessary to undertake studies both in the field of optimisation of the tea manufacturing process as well as monitoring the quality of the tea available on the market. It would also be useful to seek effective extraction methods and the selection of the optimal parameters to brew tea to obtain infusions which are the most valuable for human health.
# Self-Supervised Keypoint Learning for the Geometric Analysis of Road-Marking Templates
## 3 Methodology
### Evaluation Metrics
#### 3.7.2. Keypoint-Matching Comparison  
To highlight the advantage of our learned, semantically defined keypoints on templates over traditional feature detectors (like SIFT and ORB) for establishing robust geometric correspondence, we compare their performances in the synthetic template test set. For traditional methods, this involves detecting features on both the source template and its transformed-target version, computing descriptors, matching descriptors (e.g., using nearest neighbor matching with a ratio test for SIFT or the Hamming distance for ORB) and then using RANSAC to estimate an affine transformation from the putative matches and identify inliers. For traditional RANSAC-based methods, \(M_{i}\) is the number of RANSAC inliers found for image pair \(i\). Our method bypasses the matching and RANSAC steps by assuming a direct correspondence between the \(k\)th learned keypoint on the source and target templates; however, the number of usable keypoints (\(M_{i}\)) obtained from the model's output can vary per image pair.  
The metric used for comparison is the percentage of image pairs with sufficient matches for transformation. For each pair of source and target-transformed template images in the test set, we assess whether the number of successfully localized and usable keypoints (\(M_{i}\)) derived for that pair meets at least the minimum required number (\(N_{min}\)) necessary to estimate the geometric transformation (e.g., \(N_{min}=4\) for affine transformations). For a given GeoTemplateKPNet configuration (Backbone, K), \(M_{i}\) is the number of successfully localized and usable keypoints derived from the model's output for pair \(i\).  
Let \(N_{test}^{synth}\) be the total number of image pairs in the synthetic test set. For each image pair \(i\in\{1,\dots,N_{test}^{synth}\}\), let \(M_{i}\) be the number of sufficient matches (i.e., successfully localized and usable keypoints for GeoTemplateKPNet and RANSAC inliers for traditional methods) found using a given method. Let \(N_{min}\) be the minimum required number of matches (e.g., \(N_{min}\in\{3,4,5\}\)). The percentage of image pairs with sufficient matches is calculated as follows:  
\[\text{Success Rate}=\frac{1}{N_{test}^{synth}}\sum_{i=1}^{N_{test}^{synth}}S (M_{i},N_{min})\times 100\% \tag{12}\]  
where \(S(M_{i},N_{min})\) is an indicator function defined as  
\[S(M_{i},N_{min})=\begin{cases}1&\text{if }M_{i}\geq N_{min}\\ 0&\text{if }M_{i}<N_{min}\end{cases}\]  
A pair is considered as successful if the number of matches found (\(M_{i}\)) is greater than or equal to the minimum requirement (\(N_{min}\)). This metric directly demonstrates the reliability of different approaches in providing the foundational correspondences needed for alignment on template data. For GeoTemplateKPNet configurations (Backbone, K), the single 'rate' value reported in the results corresponds to the success rate where \(M_{i}\geq K\).