esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Discussion
### Crop Type/LC Classification Assessment
Therefore, due to the high accuracy in crop classification mapping obtained in this work a transferability can be applied for monitoring different agricultural contexts in other regions or countries. Moreover, GEE generated good crop maps even if areas was characterized by having high rainfall and cloudy weather. However, for a national scale such Thailand, with high cloud cover and small field sizes (<1 ha) and complex landscapes, the GEE is still challenging due to several limitations (i.e., data availability, processing time, and potential inaccuracies). Future studies should consider these points for improving the accuracy of crop type map results. [PERSON], et al. [11] in order to increase spectral and temporal information for crop type/LC mapping suggested to use Landsat-9 data. Specifically, they obtain outstanding results in the 2021 crop type classification in Udon Thani Province (Thailand). However, the constraint of this study was limited to cloud cover conditions, leading to image distortions of spectral reflectance. Considering the variables useful to generate a crop classification map, in this work we highlight that maxNDVI variable result to be the most important feature able to reduce cloud coverage impacts (in Appendix A Table A2). Such result is consistent with the literature, in particular [PERSON], et al. [35], [PERSON], et al. [52], [PERSON], et al. [53], [PERSON], et al. [54],highlight that maxNDVI feature overcomes the cloudy impacts for regional to global crop type or LC classifications. Considering crop types/LC classifications carried out in Thailand present in literature [PERSON], et al. [55] mapped four major classes (i.e., urban, crop, forest and water) in Thailand's Eastern Economic Corridor (EEC) obtaining \(>\) 90% of OA using convolutional neural network (CNN) and satellite images. [PERSON], et al. [56] classified LC (six classes including agricultural land, built-up area, forest, para rubber, maize, and water) using the RF classifier and multiple satellite data (S1, S2 and Landsat data) for Nan province (small region), obtaining an OA range between 52-97%. [PERSON], et al. [57] generated a crop classification map based on the RF algorithm by combining S1 and S2 data. In particular they focus their attention on sugarcane and cassava crop in a small area (Khon Kean province) and obtain an OA equal to 68%. However, in this last work the authors produced a few crop type classes and did not measure optimized-feature RF classification models for a large-scale mapping. Results obtained in this work appear to be very high in comparison to those mentioned above. Despite several crop mapped classes (eight crop type classes) excellent results were obtained by optimizing RF model and involving all available Landsat data in a large region within Thailand. Specifically, cassava and sugarcane crop classes achieved an OA \(>\) 75% turning out to be one of the best results compared to those presented by similar work [57].
# An Improved Routing Approach for Enhancing QoS Performance for D2D Communication in B5G Networks
## 4 Results and Discussion  
This section elaborates the results of the MBLCR scheme and compares its effectiveness to conventional routing schemes by employing different device speeds. The obtained results of the routing schemes are compared in terms of performance evaluation metrics, as stated in the methodology section. The following subsections describe the comprehensive and critical analysis of the obtained simulation results.
# Pipe Routing with Topology Control for Decentralized and Autonomous UAV Networks +
## 8 Simulation Results and Discussion
### Effect of Node Failures on Performance  
Next, we study the impact of node failures on the routing and coverage performance of each scheme. We select 20% or 30% of the nodes to fail at random during the simulation, to mimic the effects of energy depletion or mechanical failures, and observe that the PDR and coverage performances degrade gracefully as more UAVs fail. Note that critical path failures in case of high failure rates where connectivity to the BS could be lost are handled by the BS-CAP mobility model through its BS connectivity constraint. Additionally, the TC-Pipe routing scheme maintains the pipe region around the routes through topology management, providing alternate routes.  
For compactness, we list results only for medium distance targets in single-flow (\(C_{2}\)) and three-flow (\(C_{5}\)) settings and a higher speed. Figure 16 shows the PDR performance of each scheme, while Figure 17 shows the other routing and coverage metrics. We can see that at any given data rate, the PDR and route up time decrease and route breaks increase as more nodes fail. The impact on total coverage \(C_{v}\) is limited, but the fairness \(F\) also decreases with more failures. These effects are larger at low density than at higher UAV density.  
With more targets (\(C_{5}\)), the general trends remain similar to the single-target case; however, since more nodes are required to maintain the pipe regions, node failures can have a greater impact on the routing and coverage performances of Pipe and TC-Pipe. A higher density (50 UAVs) improves overall performance, but the impact of node failures remains visible, especially at higher failure rates.  
In the Relay scheme, the relay UAVs establish stable routes, so PDR and other routing performances see only slight decreases due to node failures. However, since more UAVs are reassigned as relay nodes, fewer UAVs are available for coverage, causing a considerable decrease in coverage compared to Pipe and TC-Pipe, especially for longer route lengths (see, e.g., the values \(C_{v}\) and \(F\) in Figure 17).  
Figure 16: PDR values for UAV speed of 40 m/s with 30 and 50 UAVs, for single-target setting \(C_{2}\) and three-target setting \(C_{5}\).  
Figure 17: Routing and Coverage metrics for UAV speed of 40 m/s, with 30 and 50 UAVs, for single-target setting \(C_{2}\) and three-target setting \(C_{5}\).
## 3 Results of the Design Verification of the Proposed Solutions  
### Cutting Insert's Factor of Safety  
The maximum and minimum values of principal stresses \(P_{1}\), \(P_{2}\), and \(P_{3}\) obtained as a result of the stress simulation are provided for all selected cutting modes in Figure 12, with a visual example of the principal stress effect on the insert body shown in Figure 13.  
Figure 11: Labyrinth seal check setup.  
Figure 12: Principal stress values, obtained from the simulation.  
The possibility of catastrophic failure as stress \(P_{1\ max}\) exceeded the tensile strength limit of the insert material (Table 3) existed only at the 0.6 mm/tooth tool feed rate and the 4.0 mm depth of cut for the rake wall thickness \(H\) equal to 0.60 and 0.55 mm (instances exceeding the limit values of \(P_{1\ max}\) are noted in Figure 12c). Based on the graphs, it is possible to observe a pronounced effect of the feed rate on the growth of the principal stress values \(P_{1\ max}\) and \(P_{3\ min}\) at the 4.0 mm depth of cut, which is associated with the largest size of the simulated contact area between the tool and the workpiece.  
The results of determining the cutting insert's factor of safety at different front wall thicknesses \(H\) using the three previously selected failure criteria (_Mohr-Coulomb_, \(FoS_{P_{1\ max}}\), \(FoS_{P_{3\ min}}\)) are shown in Figure 14. The dotted line indicates the adopted minimum factor of \(FoS_{P_{3\ min}}\).  
Figure 13: Principal stress effect on the insert body.  
safety, equal to 2.0. For the 0.4 and 0.6 mm/tooth tool feed rates, the factor of safety tended to decrease with increasing depth of cut. The final evaluation of the results was carried out using the unified Table 5.  
The factor of safety for each tested rake wall thickness \(H\) had two states according to the _Mohr-Coulomb_ criterion and three states according to the combined \(FoS_{P_{1\_mx}}\) and \(FoS_{P_{3\_mx}}\) criteria. Despite the difference in the criteria calculation methodology, the obtained test results are consistent (assuming only \(H\) thicknesses with factor of safety values greater than 2.0 were accepted as reliable).  
At the 0.2 mm/tooth tool feed rate and all depths of cut (1.0, 2.0, 4.0 mm), the factor of safety exceeded the value of 2.0, which allowed the minimum thickness \(H\) of the insert's rake wall equal to 0.55 mm to be used. At the same time, for the 0.4 mm/tooth tool feed rate, the use of the thickness \(H\) of 0.55 mm was possible only for the 1.0 and 2.0 mm depths of cut. For the 4.0 mm depth of cut, the minimum possible thickness \(H\) was 0.75 mm. At the 0.6 mm/tooth tool feed rate, the thickness \(H\) of 0.55 mm was only possible at the 1.0 mm depth of cut. For the 2.0 mm depth of cut, the \(H\) value needed to be at least 0.9 mm. For the 4.0 mm depth of cut, no \(H\) values showed a sufficient factor of safety under the stress simulation conditions.  
Figure 14: Factor of safety results, determined from the simulation.
## 5 Conclusions  
In this work, a 28 GHz SDR beamforming antenna system was proposed for 5G, radar or IoT applications. All the analog and digital modules were properly developed and described, allowing us to obtain a system operating in the Ka band. The use of USRP enabled a flexible and versatile architecture since all its characteristics could be adjusted digitally. The experimental results have shown good agreement between the simulated and measured radiation patterns. It was possible to verify techniques to shape the beam of the array, as well as steering it, in a simple way, through the control of the signal amplitude and phase of each channel in the USRP. This system demonstrates great flexibility and scalability to be used in a wide range of equipment, especially in radar, mobile and satellite communication systems.  
Figure 13: Measurement results: (**a**) polar plot of the measured radiation patterns; (**b**) measured antenna radiation pattern for many amplitude variations.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Weight Method** & **Beam Width Measured (\({}^{\circ}\))** & **Beam Width Theoretical (\({}^{\circ}\))** \\ \hline Uniform & 17\({}^{\circ}\) & 24\({}^{\circ}\) \\ Binomial & 27\({}^{\circ}\) & 32\({}^{\circ}\) \\ Dolph–Tschebyscheff (–15 dB) & 19\({}^{\circ}\) & 26\({}^{\circ}\) \\ Dolph–Tschebyscheff (–20 dB) & 21\({}^{\circ}\) & 28\({}^{\circ}\) \\ Dolph–Tschebyscheff (–25 dB) & 22.5\({}^{\circ}\) & 30\({}^{\circ}\) \\ \hline \hline \end{tabular}
\end{table}
Table 3: Half power beam width (HPBW), measured and simulated.  
**Author Contributions:** Conceptualization, D.M., R.A., T.V. and J.N.M.; methodology, D.M., R.A. and T.V.; software, D.M., and R.A.; validation, D.M., R.A., T.V. and J.N.M.; formal analysis, D.M., and R.A.; investigation, D.M., R.A. and T.V.; resources, T.V. and J.N.M.; data curation, D.M.; writing--original draft preparation, D.M., R.A. and T.V.; writing--review and editing, T.V. and J.N.M.; visualization, T.V.; supervision, T.V. and J.N.M.; project administration, J.N.M.; funding acquisition, J.N.M. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This work was partially supported by FCT/MCTES through national funds and when applicable cofunded EU funds under the project UIDB/50008/2020-UIDP/50008/2020 and the European Regional Development Fund through the Competitiveness and Internationalization Operational Program, Regional Operational Program of Lisbon, Regional Operational Program of the Algarve, in component FEDER, and the Foundation for Science and Technology, Project RETIOT, POCI-01-0145-FEDER-016432.  
**Conflicts of Interest:** The authors declare no conflict of interest.
## 2 Materials and Methods
### Spectral-Domain Optical Coherence Tomography (SD-OCT)  
For each disk, we performed 12 cross-sectional analyses (B-scans), spaced 1 mm apart, with a commercial SD-OCT device (Thorlabs Telesto-II). The device source is a superluminescent diode with a central wavelength of 1300 nm and a bandwidth of about 100 nm. The axial resolution in the air is 5.5 \(\upmu\)m, while the lateral resolution is 13 \(\upmu\)m. The detector consists of a spectrograph made of a diffraction grating and a fast camera. The system is controlled via 64-bit software preinstalled on a high-performance computer. The 3D scanning path probe with an integrated video camera performs high-speed imaging (76 kHz) for rapid volume acquisition and live display. The XZ acquisition field of view (FOV) was 10 \(\times\) 1.50 mm\({}^{2}\) with a pixel size of 8.94 \(\times\) 3.55 \(\upmu\)m\({}^{2}\). The data were processed using ThorImage 5.0 and ImageJ software, taking into account the refractive index of each polymer (n\({}_{\text{P}\text{B}72}\) = 1.49, n\({}_{\text{P}\text{B}\text{4}4}\) = 1.48, n\({}_{\text{Z}\text{apon}}\) = 1.54) to calculate the real thickness values.
# A Taxonomy of Machine Learning Clustering Algorithms, Challenges, and Future Realms
## 2 Taxonomy of Clustering Algorithms
### Hierarchical Clustering Algorithms  
Hierarchical clustering algorithms are a type of clustering algorithm where data items will be divided into sections in a hierarchical form [27]. To create a dendrogram that shows the formulated cluster's hierarchical structure, in a top-down or bottom-up way clusters are created iteratively [15]. This clustering technique enables data exploration at various granularity levels [15]. One is the divisive method where the top-down strategy is followed, and another is an agglomerative method where the bottom-up approach is followed. The process agglomerative technique follows clusters which are formed from identical items by properly combining them repeatedly into bigger clusters to establish the hierarchy's various levels. This process continues until the full object is transformed into a particular cluster or the stopping criteria is met. The opposite is true when using a polarizing strategy.  
Iteratively, the cluster comprising all the objects is dispersed until either the halting requirement is satisfied, or each object creates its own cluster. The cluster element's closeness or dissimilarity is used to determine whether to merge or split the data.  
The distance among the points of subgroups is calculated from the distance of individual points, hierarchy clustering allows for the merging or splitting of subsets of a point. The linkage metric, which measures proximity, is used to ascertain this. There are three kinds of linkages: one of them is single linkage, the second one is average connection and the last is complete linkage which is usually used in hierarchical clustering [15; 28; 29; 30; 31]. The algorithm for hierarchical clustering utilizes \(n^{*}n\) the linkage metrics utilized for the clustering are created in connectivity matrix form. Finding the similarities between each pair of data points allows for the building of the similarity matrix. When deciding on a linking criterion, it is common practice to measure the pairwise distance between each cluster. Using the measure of similarity, we may determine the separation between the groups of clusters. It is also utilized to answer the question of how the clusters themselves take form.
# An Effective ELECTRA-Based Pipeline for Sentiment Analysis of Tourist Attraction Reviews
## 2 Background and Related Works
### Text Pre-Processing  
Text pre-processing, especially for informal texts, is an integral step in sentiment analysis and PLMs. The pre-processing that may be involved includes tokenization, part-of-speech tagging, stemming, lemmatization, text cleaning [33], text clarity [34], tagging [35], lexical-grammatical check, spellchecking, stopword removal and negation handling [36]. Pre-processing has a direct impact on the performance of sentiment classification. For instance, Reference [33] indicates that the inappropriate processing of negations leads to biases and misclassification of sentiments. Reference [34] proposes cleaning and normalizing data, negation handling and intensification handling to improve sentiment classification performance. Several studies have shown that pre-processing also contributes to the performance of pre-trained models. Reference [35] leverages lexical simplification to effectively improve the performance of PLMs in text classification. Pre-processing has been verified to solve the limitations of word embedding for affective tasks [36]. Nowadays, the pre-processing of sentiment analysis mainly focuses on English text, and there are only a few works for Chinese text. Reference [37] proposes a method based on Chinese characters rather than words to address the problem of requiring complex pre-processing steps in Chinese text sentiment analysis. Reference [38] studies text pre-processing in Chinese, such as document segmentation, word segmentation and text representation, but only to unify the format of documents before text classification.
# Modeling a Pre-Touch Reaction Distance around Socially Touchable Upper Body Parts of a Robot
## 3 Materials and Methods
### Data Collection
#### 3.1.5 Hypotheses and Predictions  
We hypothesized that the minimum comfortable distance is different due to the body part in the pre-touch proxemics modeling process around the upper body parts. Past studies reported that which body part is acceptable for being touched is different based on relationships [18; 39]. Due to these studies, strangers were restricted to touching only the hands, regardless of cultural differences (East Asian and Western cultures), i.e., some might not welcome touches to their shoulders and elbows, and such hesitation would increase the minimum comfortable distance. Based on these considerations, we made the following hypothesis about the minimum comfortable distance.  
Figure 2: Data collection environment: (**a**) markers attached to both touched and evaluator; (**b**) touches is moving her hands toward evaluator’s body; (**c**) data collection setup using two OptiTrack systems for tracking both.  
Prediction 1: The minimum comfortable distance around the hands is smaller than around the shoulders and elbows.
## 5 Conclusions  
This paper explores rectification strategies with different control algorithms for the free-piston internal combustion linear power generation system. Aiming to handle the output characteristics of the linear motor within the system, it delves into three strategies: uncontrolled rectification, PWM rectification with PI control, and a compound strategy combining model predictive control and sliding mode control. The key conclusions are as follows:  
1. Uncontrolled rectification can convert three-phase AC to DC, but due to open-loop control, the output DC voltage is uncontrollable and fluctuates greatly, influenced by the linear motor's characteristics.
2. Uncontrolled rectification will cause serious current disruption in the linear motor side of the system.
3. Model predictive sliding mode compound control enhances the system's anti-interference capability. Compared to traditional PWM rectification, it offers faster response, better robustness, lower bus voltage ripple, and superior power quality.
4. Model predictive control and sliding mode control are nonlinear control methods. They adapt better in nonlinear settings like free-piston internal combustion linear power generation systems.  
Conceptualization, B.J. and Z.Z.; methodology, Y.W. and L.S.; software, L.S.; validation, L.S., J.M. and Q.L.; formal analysis, H.F.; investigation, H.F.; resources, H.F.; data curation, L.S.; writing--original draft preparation, L.S.; writing--review and editing, B.J., Y.W. and J.L.; visualization, Y.W.; supervision, J.L. and J.M.; project administration, B.J.; funding acquisition, Y.W. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Figure 26: Fluctuations in Bus Voltage Before and After Voltage Steps.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Dataset available on request from the authors.  
**Acknowledgments:** We thank the SSRN preprint platform for providing support and resources, allowing us to share our preliminary findings and receive valuable feedback ([PERSON], [PERSON] and [PERSON], [PERSON] and [PERSON], [PERSON] and [PERSON], [PERSON] and [PERSON], [PERSON] and [PERSON], [PERSON] and [PERSON], [PERSON] and [PERSON], [PERSON], Demonstration of an Advanced Rectification Strategy on a Linear Generator for Better Electricity Quality. Available at SSRN: [[https://ssrn.com/abstract=4838401](https://ssrn.com/abstract=4838401)]([https://ssrn.com/abstract=4838401](https://ssrn.com/abstract=4838401)) (22 May 2024)).  
**Conflicts of Interest:** The authors declare no conflict of interest.
# An Improved Hybrid Routing Protocol Combining MANET and DTN
## 5 Conclusions and Future Works  
In this paper, an improved hybrid routing protocol combining MANET and DTN was proposed. Then, the performance of the proposed protocol was compared from the aspects of delivery ratio, overhead ratio, and delivery latency. It was shown that the proposed protocol with appropriate selection of delivery predictability threshold values has better delivery ratio than HSBR protocol, at the expense of overhead ratio, and has similar delivery latency with HSBR protocol in the considered parameter setting. The result of this study can be used for an environment, such as disaster scenario or military scenario, where MANET and DTN should be used together in a hybrid way. In a disaster scenario or military scenario, infrastructure may not work well, and the connectivity between neighboring nodes is not stable. Thus, MANET can be used when the routing path to the destination node is available. Otherwise, DTN can be used, and a message can be delivered using store-carry-forward approach.  
In our future work, we will study about how to select the delivery predictability threshold value dynamically in varying scenarios to adapt varying network environment well. In addition, fault tolerance of the proposed protocol will be studied in our future work, too, since mobile nodes may not work well due to either the battery power problem or the destruction of mobile nodes, and the analysis of the effect of this fault on the proposed protocol is important for the application of a real disaster or military scenario. Finally, mathematical modeling and analysis of the proposed protocol and optimization will be carried out, too.  
M.W.K. and Y.W.C. conceived and designed the proposed scheme; M.W.K and Y.W.C. conceived and designed the simulations; M.W.K. performed the simulations; M.W.K. and Y.W.C. analyzed the data; M.W.K. and Y.W.C. wrote the paper. All authors have read and agree to the published version of the manuscript.  
**Acknowledgments:** This work has been supported by the Future Combat System Network Technology Research Center program of Defense Acquisition Program Administration and Agency for Defense Development (UD190033 ED).  
**Conflicts of Interest:** The authors declare no conflicts of interest.
## 3 Problem Formulation
### Structure Cohesiveness  
The commonly used structural cohesion matrices include k-clique, k-truss, and k-core. Due to its fast calculation and wide applications, we adopt k-core as a structural cohesion matrix in this paper. However, k-core is not always connected, so we only consider the connected k-core as a community.  
**Definition 1**.: _(Connected k-core) Given a graph \(G\) and a non-negative integer \(k\), a connected k-core is a connected subgraph \(H\) of graph \(G\), where \(\forall v\in E_{H},\ deg_{H}(v)\geq k\)._  
In our algorithm, k-core can be easily replaced by other structural cohesion indicators to meet the structural requirements of different scenarios.