esa-sceva/satcom-chunk-collection huggingface dataset:
# ASHM-YOLOv9: A Detection Model for Strawberry in Greenhouses at Multiple Stages
## 4 Experiments and Results
### Contrasting Model Performance Prior to and Following Enhancement
This shows that our enhanced model is better suited to meet the needs of multistage strawberry recognition in agriculture. Figure 11 shows the F1 confidence curves of YOLOv9 (Figure 11a) and ASHM-YOLOv9 (Figure 11b). The horizontal axis represents the confidence level, and the vertical axis represents the F1 score, which integrates precision and recall. By comparison, the overall F1 score of ASHM-YOLOv9 reaches 0.98 and can be achieved at a \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{4}{c}{**Mature Stage/\%**} \\ \hline
**Models** & **Precision** & **Recall** & **mAP50** & **mAP50-95** \\ \hline YOLOv5s & 98.5 & 98.0 & **99.4** & 84.9 \\ YOLOv7 & 98.3 & 96.6 & 95.4 & 84.5 \\ YOLOv8n & 98.6 & 97.0 & 99.1 & 88.5 \\ YOLOv9c & 98.7 & 95.9 & 99.2 & 85.5 \\ ASHM-YOLOv9 & **98.8** & **98.4** & 99.2 & **92.4** \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Experimental results for each model at the mature stage. \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{4}{c}{**Whole Stage/\%**} \\ \hline
**Models** & **Precision** & **Recall** & **mAP50** & **mAP50-95** \\ \hline YOLOv5s & 97.3 & **97.3** & 98.8 & 82.8 \\ YOLOv7 & 96.7 & 95.0 & 96.5 & 82.6 \\ YOLOv8n & 97.2 & 95.1 & 98.4 & 85.7 \\ YOLOv9c & 97.1 & 94.2 & 98.4 & 83.3 \\ ASHM-YOLOv9 & **97.7** & 97.2 & **99.1** & **90.7** \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Experimental results for each model at the whole stage. \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{4}{c}{**Growth Stage/\%**} \\ \hline
**Models** & **Precision** & **Recall** & **mAP50** & **mAP50-95** \\ \hline YOLOv5s & 95.9 & 96.2 & 98.8 & 83.7 \\ YOLOv7 & 95.0 & 92.4 & 97.2 & 82.6 \\ YOLOv8n & 95.7 & 94.1 & 97.6 & 86.3 \\ YOLOv9c & 95.3 & 93.5 & 98.1 & 84.4 \\ ASHM-YOLOv9 & **96.5** & **97.1** & **99.1** & **91.6** \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Experimental results for each model at the growth stage. confidence threshold of 0.265; the overall F1 score of YOLOv9 is 0.97, requiring a confidence threshold of 0.566. This finding indicates that ASHM-YOLOv9 has a better balance between confidence and performance. The curves of various classes (flower, growth, mature) also show that its single-class performance may be improved, and the overall performance is better than that of YOLOv9.
# A Symbol Recognition System for Single-Line Diagrams Developed Using a Deep-Learning Approach
## 2 Related Works
### Digitization of Engineering Documents
Another approach utilized a fully linked convolutional neural network to develop symbol localization techniques [42]. A dataset comprising 672 process flow drawings was used to automate engineering drawings, resulting in improved performance compared to conventional methods. However, accurate detection of all components was not achieved, and the class accuracy for different components in the drawings was around 64.0%. To capture the time-varying signal produced by pen movements during the sketching process of a one-line hand-drawn electrical circuit diagram, hidden Markov models (HMMs) were utilized [43]. A dataset containing 100 hand-drawn sketches was examined for this purpose. The proposed approach, which employed HMMs, yielded promising outcomes. Itachieved an accuracy of more than 83% in classifying the points associated with connector and symbol categories correctly. A circuit-diagram recognition system was developed to address sketch recognition as a dynamic programming problem, incorporating a novel technique called 2D-DP [44]. The 2D-DP technique demonstrated successful identification of interspersed symbols within the sketches. The method introduced a tolerant connectivity function cost, which proved effective in recognizing free-form sketches. The experiment involved analyzing 130 sketches containing ten different types of electrical symbols. Point-level measurements revealed that the novel approach achieved an accuracy of over 90 percent. A grammar-based parsing strategy for recognition of hand-drawn one-line diagrams was introduced to evaluate the system on UML use-case diagrams, showing an improved recognition accuracy [45]. However, further accurate and formal user studies are necessary to understand the strategy's limitations and explore potential enhancements. The adoption of advanced deep-learning methodologies has resulted in significant improvements in the detection and recognition of notations and symbols in musical documents [46]. Techniques such as Faster R-CNNs, R-FCNs, YOLO, and SSD have been successfully applied to identify handwritten musical symbols, demonstrating superior performance compared to traditional structured image processing methods for symbol recognition and detection [21; 47]. In summary, the existing research highlights a notable gap between the current state of machine learning and technical image comprehension. This discrepancy arises from the rapid progress in the field juxtaposed with the uneven and incremental advancements in a critical application area that has implications across various sectors.
## 1 Introduction and Literature Review
The complex three-dimensional geometry of propeller blades also poses numerous challenges in terms of the design of inspection equipment. Such equipment must be capable of high precision, high repeatability, multidirectional measurement, automatic control, data collection and analysis, safety, and ease of maintenance. To meet these requirements, the present study incorporated ball screw linear stages, servo motors, flange-type planetary reducers, coaxial planetary reducers, and an integrated programmable logic controller (PLC) with a human-machine interface (HMI). These components are adopted in coordination with a CITIZEN displacement sensor. In addition, mechanical probes are used as the primary measurement tool because of their high precision, fast response, reliability, broad applicability, and ease of implementation. Of the various practices currently employed, mechanical probes are those most commonly used for automatic tool center positioning [17]. The feedback information provided by these probes can be used to adjust the motion of robotic arms and accurately locate the tool. In large-scale production environments, measurement efficiency can be improved using an online network for the storage, transmission, and analysis of inspection data. This approach effectively reduces the burden of manual data processing and, when integrated with a cloud-based automated system, enables real-time monitoring and immediate optimization. To clearly illustrate the entire production process and highlight where our proposed system introduces new measurement steps, Figure 1 shows the full process flowchart for precision casting of marine propellers. In this workflow, we have added three key inspection stages--Step 5: Wax Pattern Measurement, Step 9: Raw Casting Measurement, and Step 16: Product Measurement--which allow for real-time tracking of dimensional deformation throughout the manufacturing process. These additions emphasize the motivation for developing a real-time online measurement system and underscore the importance of integrating automated inspection into traditional production flows.
# A CIOS Analysis for the Promotion of Sustainable Plans of Mobility: The Case of Mexico City
## 3 Results
### Representation Phase
#### 3.1.1 System's Explanation
Thus, all the circulating units are going to be equipped with Global Positioning System (GPS) platforms that will be available to the public for monitoring operation and verification of routes;  
Figure 3: The sustainable urban mobility plan of Mexico City. 4. policy oriented towards the promotion of walking and cycling, this policy consists of the expansion of bike lanes network and the establishment of bicycle parking places next to mass transit stations (intermodalism). The improve strategy depends on the public policies seen in the following lines:  
1. improvement of public transport systems; this policy is oriented towards the enhancement of public transport via the acquisition of new units (100 units for the electric transportation modes and 800 units for the public bus systems) as well as a periodical metro maintenance. Furthermore, this policy considers the remodelling of 2 modal transfer centres, the management of agglomerations in at least five Bus Rapid Transit (BRT) stations, and the implementation of exclusive lanes for public transport;
2. transit and parking places management policy, which is aimed at the integration of automated traffic light systems and the integration of parking-meter systems;
3. policy for regulation and improvement of private mobility services; this policy considers the proposal for comprehensive regulation of taxi services and the publication of guidelines for the operation of bicycle systems and micromobility vehicles;
4. policy of innovation and technological improvement, contemplating the installation of the control and innovation centre of mobility in Mexico City, as well as, the release of public transport's open data. Furthermore, this policy takes into account the establishment of comprehensive programs related to electric mobility and smart mobility in Mexico City;
5. comprehensive policy of freight transport, which is based on the publication of the strategic cargo plan for Mexico City;
6. citizen attention policy, which considers the geographic expansion of care centres. While the protect strategy is based on the following public policies:  
1. safe streets policy, which considers the establishment of safe infrastructure with elements of universal accessibility for walking and cycling;
2. road safety policy that is oriented to the behaviour change of drivers via the implementation of the good driver's decelogue and the establishment of a system of civic sanctions;
3. mobility with gender perspective policy, aimed at an improved perception of safety levels among the female public transport users, through the prevention of harassment in the transportation system of Mexico City.
## 3 Development of RF WPT-Enabled IoT Application
### Implementation and Experimental Validation
#### 3.4.2 Antennas for RF Energy Transfer  
The antennas of both the base station and the IoT node are the key elements, affecting the efficiency of the WPT. Depending on the number of the nodes served by a single WPT transmitter and whether the location of all the IoT nodes is known and static, one can use two different approaches. The former one is based on the use of omnidirectional antennas and is intended for the case when the nodes are uniformly scattered around the base station or are highly mobile. As analyzed, e.g., in Ref. [46], this approach is characterized by the minimum energy transfer efficiency. The use of directive antennas enables increasing the WPT efficiency (refer, e.g., to Ref. [63]) but is sensible only if the location of the nodes is known or if they are clustered most of the time. Finally, a combination of these techniques (e.g., use of directive antennas for base station and omnidirectional on the nodes, or vice versa) can be considered for particular use cases. Note that the requirements of the real-life applications often limit the antenna dimensions, thus putting a limit on antenna's efficiency.  
Given the geometry of our target application setup, the use of directive antennas is reasonable. The conducted market analyses have shown that no directive 868 MHz band commercial antennas are available. Due to this reason, we designed and prototyped our own linearly-polarized patch antenna, layout, and dimensions, which are illustrated in Figure 6. The reason for us basing our design on the patch antenna was twofold. First, this type of antenna is known to feature higher directivity than the dipoles. At the very same time, these antennas are still sufficiently simple and technological for mass-scale production.  
The designed antenna was first simulated in SW, and then two pieces have been manufactured using a low loss Rogers RT5880 substrate (\(\epsilon=2.20\), loss \(\delta=0.0009\)) with 3.1 mm substrate thickness and a 35 \(\upmu\)m copper cladding. The dimensions of the ground plane are \(200\times 200\) mm\({}^{2}\) and the dimensions of the radiator are \(172\times 112\) mm\({}^{2}\). A large ground plane surface increases the antenna size but also enables a more directive beam and makes the characteristics of the antenna less dependent on mounting location and environment. This makes the antenna better fit our targeted environment. The 50 Ohm coaxial line is used to feed the antenna. One of the manufactured antennas is depicted in Figure 7.  
Figure 6: Layout and dimensions of the designed antenna.
# Electrospinning-Based Carbon Nanofibers for Energy and Sensor Applications
## 2 Electrospinning of Carbon Precursor Polymer
### Polymer Nanofibers for Carbon Nanofibers
#### 2.2.3 Pitch-Based Carbon Nanofibers  
Pitch, a viscoelastic polymer, can be derived from a natural source such as petroleum, coal tar, or plants. Although the other types of processors can be dissolved into a solvent to make a polymer solution for electrospinning, the pitch cannot be dissolved in any solvent and must be processed into fibers using the melt-spinning method. This requirement has limited the application of the pitch for the production of fibers as it requires a high temperature. The spinning temperature can vary between 300 and 350 \({}^{\circ}\)C, slightly higher than the pitch's softening temperature [47]. Before being used in an electrospinning system, the pitch usually undergoes heat treatment to increase the molecular weight of the polymer chain [48]. Just as the softening point changes depending on the properties of the processed pitch material, the carbonization temperature is different between the studied materials. In addition, additives such as polyvinylchloride, polystyrene, cariflex, or arbocel can affect the pitch's properties and the resulting carbonized fibers.
# Impact Analysis of Satellite Geometry Variation on ARAIM Integrity Risk over Exposure Interval
## 3 Integrity Risk Evaluation over the Exposure Interval
### Hazardous Misleading Information
This conservative definition is commonly employed to rigorously analyze the integrity performance of ARAIM [20]. Compared to (3), the conservative definition mainly has the following advantages: Firstly, this definition is currently used by the NES-based ARAIM to evaluate integrity risk, and its conservative nature ensure the reliability of the analysis results. Secondly, when evaluating integrity risk based on this definition, all positioning errors under different fault mode hypotheses are considered fault-free, thus eliminating the need to search for the worst-case fault. Therefore, we will adopt the conservative definition to conduct integrity risk evaluation in this paper.
## 3 Results
### Verification of HRSIF  
#### 3.2.1 Comparison with Ground-Based Observations  
Satellite SIF observation is a regional and large-scale remote sensing method. Therefore, to verify the accuracy of its data, it is necessary to conduct cross-validation using near-surface in situ observations. The downscaled SIF (hereinafter referred to as HRSIF) data can better meet the requirements for such comparisons. Considering the high-frequency daily observations at these sites, we calculated the average of all SIF measurements between 9:00 AM and 10:00 AM local time to represent the daily observation value, corresponding to the GOME-2 overpass time (approximately 9:30 AM). These daily values were then aggregated into 8-day averages to match the spatial and temporal resolution of the satellite data. The comparison between ground-based and satellite SIF data shows that their annual trends are highly consistent, with strong correlations between the two datasets, as shown in Figure 4. The US-NR1 and CA-OBS sites are both dominated by evergreen needleleaf forests (ENF), with highly consistent vegetation cover, leading to the strongest correlations. The Huailai and Jurong sites are cropland ecosystems, which are more affected by human activities, resulting in relatively lower correlations.
## 2 Results and Discussion
### Concluding Computational Studies  
Among the compounds tested, dioscin was shown to be a very promising candidate for reducing \(H\). _pylori_ biofilm formation and sensitizing to certain antibiotics. This substance was shown to be the most promising during molecular docking experiments since it had one of the lowest binding free energies of \(-9.8\) kcal/mol. Only madecassoside was discovered to have a lower value (\(-10.6\) kcal/mol) and shall be considered for further studies as a potent SpoT inhibitor.  
Figure 8 illustrates our hit's interactions with the binding pocket, using coloring schemes adequate to those discussed earlier. The hit and natural ligands shared four amino acids: ARG77, ARG61, GLN133, and ARG48. Although just two hydrogen bonds, interacting with dioscin saccharides, have been discovered in this binding mechanism, they arise from the amino groups of ARG48 and ARG77, just as they do for ATP and GTP, suggesting their relevance for the binding mode. Instead, we observed a number of van der Waals interactions, which underlined that the binding mechanism is strongly hydrophobic.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Tested Combination**} & \multicolumn{6}{c}{**MIC [ug/mL]**} & \multirow{2}{*}{**FICI**} \\ \cline{2-2} \cline{4-7}  & & \multicolumn{2}{c}{**Dioscin**} & & \multicolumn{2}{c}{**Antibiotic**} & \multirow{2}{*}{**(Outcome)**} \\ \cline{2-2} \cline{4-7}  & **Alone** & **Combination** & **Fold Change** & **Alone** & **Combination** & **Fold Change** \\ \hline Dioscin + & \multirow{2}{*}{64} & \multirow{2}{*}{32} & \multirow{2}{*}{2} & \multirow{2}{*}{0.025} & \multirow{2}{*}{0.006} & \multirow{2}{*}{4} & 0.75 \\ CLR & & & & & & & (additive) \\ \hline Dioscin + MTZ & \multirow{2}{*}{64} & \multirow{2}{*}{16} & \multirow{2}{*}{4} & \multirow{2}{*}{1} & \multirow{2}{*}{0.5} & \multirow{2}{*}{2} & 0.75 \\  & & & & & & & (additive) \\ \hline Dioscin + & \multirow{2}{*}{64} & \multirow{2}{*}{32} & \multirow{2}{*}{2} & \multirow{2}{*}{1} & \multirow{2}{*}{0.5} & \multirow{2}{*}{2} & 1.0 \\ LEV & & & & & & (additive) \\ \hline \hline \end{tabular}  
* The fractional inhibitory concentration index (FICI) values of \(\leq 0.5\), \(>0.5\) to \(\leq 1\), and \(>1\) to \(\leq 4\) were expressed as synergistic, additive, and neutral, respectively.  
\end{table}
Table 3: Numerical values showing interactions between dioscin and the three classically used antibiotics (clarithromycin [CLR], metronidazolezole [MTZ], and levofloxacin [LEV]) in antibacterial activity against \(H\). _pylori_ j99. Interactions were determined using the checkerboard assay.  
Figure 7: Graphics showing the interactions between dioscin and the three classically used antibiotics (clarithromycin [CLR], metronidazolezole [MTZ], and levofloxacin [LEV]) in antibacterial activity against \(H\). _pylori_ j99. Interactions were determined using the checkerboard assay. FICI values of \(\leq\) 0.5, \(>\) 0.5 to \(\leq\) 1, and \(>\) 1 to \(\leq\) 4 were expressed as synergistic, additive, and neutral, respectively.
## 4 Discussion
### Analysis of Clean Surface  
Surface contaminants, especially ionic contaminants, may have a significant impact on the entire ion migration process. However, ionic contaminants may not be essential for migration compared to the presence of water. In the test, we found that the sampling value of the uncontaminated sample changed at 85 \({}^{\circ}\)C/90% RH and 95% RH. Moreover, in the rapid alternating damp heat test, the change value was greatly increased. This indicates that under these conditions, ion migration occurs on the surface of PCB.  
On the one hand, pure water has a fairly low conductivity through the proton jumping mechanism [37], as shown in Equation (6):  
\[H_{2}O+H_{2}O^{+}\to H_{2}O^{+}+H_{2}O \tag{6}\]  
On the other hand, water would further exacerbate conductivity if it absorbs from the atmosphere gases with which it forms compounds such as CO\({}_{2}\)[38].  
\[CO_{2}\ +H_{2}O\leftrightarrow H_{2}CO_{3} \tag{7}\]  
\[H_{2}CO_{3}\leftrightarrow H^{+}+HCO_{3}^{-} \tag{8}\]  
The conductivity of water is related to the thickness of the water film [39]. In the rapid alternating damp heat test, there were condensed water droplets (bulk water) on the surface of the PCB, and the thickness of the water layer was much thicker than the thickness of the water film adsorbed on the PCB under the condition of constant temperature and humidity. This is why the sampling value changed much more in the rapid alternating test than under constant temperature and humidity conditions.  
Figure 21: Contact Angle of an uncontaminated sample, and 20 \(\upmu\)g/cm\({}^{2}\) and 50 \(\upmu\)g/cm\({}^{2}\) samples.  
Figure 22: Contact angle at different pollution concentrations.  
It can be seen defining the uncontaminated sample as having ionic contamination at a concentration of less than 1.56 \(\mathrm{\SIUnitSymbolMicro g}\)/cm\({}^{2}\) is not completely appropriate. The limit of 1.56 \(\mathrm{\SIUnitSymbolMicro g}\)/cm\({}^{2}\) was taken from IPC-J-STD-001H. How to identify the qualified cleaning manufacturing process, and how to carry out effective protection is still a direction for future research.  
Encapsulation has proven to be an effective form of protection. Encapsulation reliability involves materials, design, process, and testing. Breakdown of the potting interface is the main failure mode of encapsulation [40]. An in-depth understanding of its breakdown mechanism, influencing factors and how to suppress them, requires further study