esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Results and Discussion
### Sentiment Analysis  
With a general perspective on data, we considered it necessary to perform an analysis of the prevalence of the most relevant emotions (happiness, sadness, fear, and anger) in the communications captured with the application. With this analysis, we can understand not only the way users communicate thanks to the application but also their main motivations for doing so. Table 18 shows the percentage of phrases that present any of the emotions previously listed for each category. We added a neutral column for those where no particular emotion stands out.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Category** & **Samples** & **Length** \\ \hline Social interaction & 650 & 6.378 \\ Nutrition & 686 & 9.370 \\ Leisure & 419 & 8.795 \\ Care & 110 & 7.745 \\ Emotions & 61 & 7.639 \\ Health & 31 & 8.903 \\ Names & 116 & 5.405 \\ \hline \hline \end{tabular}
\end{table}
Table 17: Test 6: Average length of new pictograms in the different categories.  
\begin{table}
\begin{tabular}{l c c c c} \hline \hline
**Category** & **Happiness** & **Anger** & **Sadness** & **Fear** & **Neutral** \\ \hline Social interaction & 46.46\% & 0.00\% & 0.01\% & 0.00\% & 53.53\% \\ Nutrition & 97.82\% & 0.00\% & 0.00\% & 0.00\% & 2.18\% \\ Leisure & 78.83\% & 0.00\% & 0.00\% & 0.00\% & 21.17\% \\ Care & 6.30\% & 0.00\% & 0.00\% & 0.00\% & 93.70\% \\ Emotions & 42.10\% & 2.57\% & 28.87\% & 0.60\% & 25.86\% \\ Health & 0.00\% & 0.00\% & 73.19\% & 0.00\% & 26.81\% \\ \hline \hline \end{tabular}
\end{table}
Table 18: Sentiment analysis of generation events.  
For categories such as nutrition and leisure, we observe that an overwhelming majority of the interactions have an inherently positive emotion, as they mostly express desires for food or recreation. As expected, the emotions category presents the most wide range of emotions, being the only one where anger is expressed. Finally, health stands out, as the majority of entries express sadness, which is logical, given the fact that most the associated clauses are used to express discomfort. For care and social interaction, the majority of sentences are neutral.  
We also considered conducting this analysis on newly added pictograms despite the limitation of the length of the added terms. Table 19 presents the results of this analysis.  
As the new pictograms are fractions of phrases, most of them lack complete meaning by themselves. This is why the majority are classified as neutral in all categories except emotions. We considered it interesting that the pictograms created under the latter are as evenly distributed as the generation events for the same category. In particular, the difference between the creation of new pictograms that represent anger and their use could mean that users identify a lack of predefined terms to express this emotion.
# Detection of Defective Features in Cerasus Humilis Fruit Based on Hyperspectral Imaging Technology
## 2 Materials and Methods  
### Experimental Sample  
The samples were collected from the _Cerasus humilis_ fruit planting demonstration base of Shanxi Agricultural University (3 August 2022), and the variety is \"Nongda No. 6\". To ensure the reliability of the study, samples of similar shape, uniform size (9.0-13.0 g per fruit), and complete defect type (intact, rust spot, insect damage, crack) were selected. A total of 420 samples were selected, including 92 rust spot samples, 84 insect damage samples, 84 crack samples, and 160 intact samples. Intact and defective samples are shown in Figure 1.  
Hyperspectral images of each sample were collected and assigned values of 1, 2, 3, and 4 for each of the 4 categories of data (rust spot, crack, insect damage, and intact). Four types of samples were divided into the correction set (315) and the prediction set (105) according to the ratio of 3:1 using the sample set partitioning based on joint X-Y distance (SPXY) algorithm [11]. The statistical results of sample set division were shown in Table 1.
# Big Data Integration in Remote Sensing across a Distributed Metadata-Based Spatial Infrastructure
## 2 Background on Architectures for Remote Sensing Data Integration  
This section briefly reviews the distributed integration and spatial organization model of remote sensing data, as well as the internationally popular data system framework OODT.
## 3 Results and Discussion
### Volatile Compound Composition
#### 3.1.6 Furanic Compounds, Phenolic Aldehydes, and Oak Lactones  
Like volatile phenols, furanic compounds, phenolic aldehydes, and oak lactones are also important volatile compounds that can be extracted from the oak barrel into the wine during the aging process, and these volatiles can help maturate wine by enhancing the aging aroma of the wine [34]. In the present study, five furanic compounds, four phenolic aldehydes, and two oak lactones were found in these wines. Before the aging process, only furanic and acetylfuran exhibited significantly (\(p\leq 0.05\)) higher concentrations in the clone 191 wine than in the clone 169 wine, whereas the other volatiles showed similar levels in the two clone wines. With the aging process, the concentrations of these volatilesincreased in all wines, which was a result of the extraction from the oak barrel to the wines (Figure 1f). After an aging process of 12 months, the clone 169 wines showed significantly (\(p\leq 0.05\)) higher concentrations of acetylfuran, vanillin, acetosyringone, and acetovanilone than the clone 191 wines (Table 2). Additionally, the wines aged in the Bordeaux oak barrel contained significantly higher levels of furfural, 5-methyl furfural, acetylfuran, acetovanilone, syringaldehyde, and acetosyringone, whereas higher levels of the two oak lactones were found in the wines aged in the Wolin oak barrel after the aging period.
## 3 Results and Discussion
### Visual Nanoparticle Settling Assessment  
All nanolubricants samples were observed on days 0, 1, 3, 7, 15, 30, 54, and 77 after preparation. Visible changes were not apparent until the 30 th day. Figure 4 shows a comparison of both nanolubricants samples up to 77 days after preparation for different sonication times (0 h, 1 h, and 2.5 h). On the first day of observation, all samples appeared to be dispersed well and it was difficult to differentiate them with the naked eye. Starting from the 30 th day, a small number of nanoparticles began to deposit in the form of a white layer at the bottom of the cuvettes. This sedimentation gradually increased, becoming more noticeable by the 54 th and 77 th days. It was observed that the amount of sedimentation in bio-lubricants was slightly higher than in conventional lubricants. However, the effect of different sonication times on the amount of sedimentation was not entirely clear by visual inspection alone. This difference should be measured more accurately using a UV-Vis spectrophotometer.  
Figure 4: Static stability of nanolubricant samples with different sonication times: (**a**) after preparation (Mistral 15W40); (**b**) after preparation (PLANTO MOT SAE 10W40);(**c**) after 30 days (Mistral 15W40); (**d**) after 30 days (PLANTO MOT SAE 10W40); (**e**) after 54 days (Mistral 15W40); (**f**) after 54 days (PLANTO MOT SAE 10W40); (**g**) after 77 days (Mistral 15W40); (**h**) after 77 days (PLANTO MOT SAE 10W40).
## 4 Multidisciplinary Design, Analysis, and Optimization of an Adaptive Wing
### Aerodynamic Constraints  
The formulation of the aerodynamic constraints for new airfoils is based on the flight conditions. In this paper, only the cruise flight phase of the UAV S45 will be covered. It is assumed that during the cruise flight trajectory the distributions of the lift and drag forces along the wingspan cannot exceed the limitations of the structural loads. The design optimization procedure implicitly defines the following requirements:  
1. The under-actuated airfoil shape will achieve the same lift and drag coefficients as the reference wing requirements;
2. The angle of attack will remain constant throughout the cruise flight phase;
3. The \(C_{l}\) and \(C_{d}\) improvement (variations) will be achieved through the adaptive system-controlled variation of the airfoil shape;
4. Constraints ensure that the airfoil shape remains within the structural and geometrical limitations of the wing prototype. For instance, the wing prototype will have a minimal and maximal allowed vertical displacement (\(A_{min}\), \(A_{max}\)) of \(\pm 5\) mm;
5. Based on the fitness function definition \(f=C_{L}/C_{D}\), an airfoil can subsequently be optimized to maximize this objective, and only the best aerodynamically, high-performing new airfoil shapes are experimentally tested in the Price-Paidoussis wind tunnel.  
The proposed approach developed at LARCASE to design an adaptive wing considers the interactions between aerodynamics, structures, and control. This multidisciplinary approach is used throughout the design and manufacturing optimization phases of the prototype.  
The approach outlined in Figure 7 allows the wing prototype to be designed and optimized with the aerodynamics requirements specific to the S45 cruise flight phase. From these data, the airfoil aerodynamic coefficients are calculated and used as inputs by the subsequent aero-structural optimization to determine the geometrical and structural properties of the airfoil. The key feature of our approach is that the new airfoil shapes are determined by the aero-structural optimization, the structural constraints of the actuators, and the material properties.
# Energy-Efficient Hybrid Routing Protocol for IoT Communication Systems in 5G and Beyond
## 3 Problem Formulation and Existing Challenges
### Overview of WSN and IoT Communication Systems
#### 3.1.2 Accelerated and Unbalanced Energy Consumption Issue  
Cluster Head consumes more energy over a large-scale network than its member nodes. This is because it collects and aggregates data from nodes within cluster and transfers the same data to the central station over a long distance. Therefore, clustering algorithms divide the process into rounds to equalize the energy among sensor nodes, and rotate the cluster head responsibility among the nodes inside a cluster. Nevertheless, the consumption of energy between cluster heads remains unbalanced due to multi-hop route among multiple cluster heads, in which a Cluster Head near the central station serves as a router for the rest of the sensors and the relay traffic will be overloaded. Thus, some nodes die prematurely, leading to network holes. The optimum route among the cluster heads is another issue in the multi-hop communication model, using this route for any data transmission would contribute to the energy drainage among the cluster heads.
## 3 Results and Discussions
### Results of Improvement in Tilting of Edge  
To improve the tilted-edge angle condition described in Section 3.3, a curved, single-axis stage tilted a 5.2\({}^{\circ}\) was installed. The subsequent laser cutting operation and relevant parameter selection were performed a described in Section 3.2. The laser finishing was performed in accordance with Section 3.3 and Method 3. The laser parameters were average power of 30 W, scan rate of 5 mm/s, pulse width of 200 ns, and pulse repetition rate of 30 kHz, as shown in Figure 18. The test results showed that the tilting of the edge was resolved successfully by tilting the workpiece at a specific angle during laser processing. The measurement of the cut edge after laser processing was approximately 90\({}^{\circ}\), and no significant difference in surface quality was observed between the untilted and tilted stage settings. The surface morphologies and roughness of the processed surface measured by CCI are shown in Figure 19. The surface roughness of the processed PCD workpiece with tilted stage was Ra = 0.202 \(\upmu\)m, which was similar to that in the untilted stage processing (Ra = 0.209 \(\upmu\)m).  
Based on this test, the proposed laser cutting and finishing processes could obtain a smooth and pit-free processed surface of the PCD workpiece, as shown in Figures 18 and 19. The surface morphology and surface quality (see Figure 18b) observed through SEM are very similar to those reported in the studies by [PERSON] et al. [PERSON] et al. (2017) and [PERSON] et al. [PERSON] et al. (2018) with picosecond pulse laser processing, and [PERSON] et al. [PERSON] et al. (2018, 2019) with femtosecond laser processing. The surface roughness measured in this study (see Figure 19) was similar to that in the study conducted by [PERSON] et al. [PERSON] et al. (2017) with picosecond pulse laser (surface roughness Ra = 0.16 \(\upmu\)m). Furthermore, this tilted stage method can be used in applications that require various rake angles and clearance angles in the PCD cutting tool design in the future.  
Figure 16: Optical microscope image (**a**) and SEM morphology (**b**) of the laser-finishing surface of the PCD workpiece by Method 3, using a pulse width of 200 ns and pulse repetition rate of 30 kHz.  
Figure 17: Coherence correlation interferometry measurement of surface roughness of the laser processed PCD workpiece before and after laser finishing. (**a**) Surface morphology and surface roughness before finishing (Ra = 0.378 μm); (**b**) surface morphology and surface roughness after finishing (Ra = 0.209 μm).
## 3 Results and Discussion  
### Syntheses and Characterization  
The reaction of 3-amino-2-pyrazinesarboxylic acid (HL) with iron(III) chloride hexahydrate in ethanol under reflux leads to the formation of the mononuclear [Fe(L)\({}_{3}\)] **(1)** (L = 3-amino-2-pyrazinesarboxylate). The syntheses of [NHEt\({}_{3}\)][Fe(L)\({}_{2}\)(C)]\({}_{2}\)] **(2)** and [Fe(L)\({}_{2}\)(\(\mu\)-OMe)]\({}_{2}\).DMF.1.5 MeOH **(3)** were carried at room temperature, by reacting HL with iron(III) chloride hexahydrate in the presence or absence of triethylamine in MeOH (Scheme 1). Moreover, the solvothermal reaction of HL with FeCl\({}_{3}\).6H\({}_{2}\)O in the presence of NaN\({}_{3}\) in DMF and methanol mixture leads to the formation of the 2D oxido- and aqua-bridged heterometallic Fe(III)/Na(I) coordination polymer [Fe(N\({}_{3}\))(\(\mu\)-L)\({}_{2}\)(\(\mu\)-O)\({}_{1/2}\)(Na)(\(\mu\)-H\({}_{2}\)O)\({}_{1/2}\)]\({}_{\rm In}\) **(4)** (Scheme 1).  
In the FT-IR spectra of 1-4, the characteristic strong bands of the coordinated carboxylate groups appear at 1612-1652 cm\({}^{-1}\) or 1356-1368 cm\({}^{-1}\) for the asymmetric or the symmetric stretching, respectively. Asymmetrical and symmetrical N-H stretching frequencies of the amine groups appear in the 3442-3466 cm\({}^{-1}\) region. The bands at 1319-1339 cm\({}^{-1}\) are attributed to C-N stretch (aromatic amines) [37].
# Multiple Instances QoS Routing in RPL: Application to Smart Grids +
## 1 Introduction
Other papers classify the traffic into two levels: critical and periodic [14]. Based on that and since the traffic classes in the SG are not standardized, a single solution to route the traffic with different QoS may not be sufficient since the number of instances (traffic classes) vary depending on the application and the implementation. A multi-objective solution is thus essential to meet the QoS requirements of SG applications. Therefore, in this paper, we introduce \(OFQS\) an RPL-compliant objective function, with a multi-objective metric that considers the delay and the remaining energy in the battery nodes alongside with the quality of the links. Our function automatically adapts to the number of instances (traffic classes) providing a QoS differentiation based on the different Smart Grid applications requirements. We conducted real testbed experimentations which showed that \(OFQS\) provides a low packet delivery latency and a higher packet delivery ratio while extending the lifetime of the network compared to solutions in the literature. The remaining of the paper is organized as follows: Section 2 presents first a brief overview of the RPL protocol. After that, prior works around the RPL protocol concerning the metrics and the multiple instances are provided. Finally, we present the motivations of using multiple instances in RPL. Section 3 describes our proposition in details. Section 4 shows the experiment setup and environment used to validate our proposition and its parameters. Section 5 presents the performance evaluation of our proposition and remaining issues are discussed in Section 6. Finally, Section 7 concludes the paper.
# Predictive Quantization and Symbolic Dynamics
## 2 Information Dynamics
### Latent Information Rate  
A central goal of representation learning that stems from the information dynamics principle is maximizing the amount of information passing between the encoded past \(Z\) and the next data sample \(Y\). Using the second set of Markov relations shown in Figure 4, we would like to consider here the information passing between the latent variables \(Z\) and \(T\) themselves. We express \(I(Z,Y)=I(Z,T)-I(Z,T|Y)\) as a measure of the ability to predict the future of the time series, and the next observation \(Y\) from past embedding \(Z\), compared with the information dynamics of the latent embedding time series itself. From these information relations, we see that the amount of information that past encoding \(Z\) carries out about the future observation \(Y\) is less than the amount of information carried between the past and future of the embeddings \(Z\) and \(T\) themselves. The term \(I(Z,T)\) can be considered as latent predictive information, or latent information dynamics, corresponding to some sort of a latent anticipation.  
Ignoring \(I(Z,T|Y)\) (or assuming it is zero) means that the next data observation \(Y\) causes the latent representations of the past and present to be independent. In such a case, the information \(I(Z,Y)\) contained in the latent encoding of the past \(Z\) about the present data \(Y\) is the same as the information contained in the past and present data observations \(X\) and \(Y\) directly. In such a case, the maximization of the information dynamics in the latent space \(I(Z,T)\) is sufficient for maximizing the predictive ability of the model. This assumption allows us to formulate yet another more tractable version of the predictive latent bottleneck problem  
\[\max_{P(Z|X),P(T|Y)}\{I(Z,T)-\lambda I(X,Z)\} \tag{7}\]  
where the encoding of the past and the present observations are represented by probability distributions \(P(Z|X)\) and \(P(T|Y)\), respectively. In the case when the past is encoded data point by data point independently in time, the same encoder, and thus same probability function \(P(x,z)=P(y,t)\), is used throughout the whole time series. In such a case, we can separately learn an encoder over the whole time series first; then, in the next step, we can evaluate the information dynamics of the sequence of latent variables. When performed in a iterative manner by computing the predictive information using symbolization and further altering an existing encoding using rate-distortion, an optimal final model can be found by an exhaustive search over the bit-rate and quantization threshold parameters.
# An Analog Circuit Fault Diagnosis Method Based on Circle Model and Extreme Learning Machine
## 1 Introduction
During the failure of the analog circuit, the response output collected at the output point is often nonstationary, nonlinear, and time-varying. The original signals contain redundant information and have high dimensionality. If directly applied in fault diagnosis, these signals will push up the computing load and drag down the diagnosis efficiency and accuracy. To clearly distinguish between fault modes, it is critical to effectively process fault signals by the appropriate fault feature extraction method. Through the above analysis, this paper decides to develop a novel fault diagnosis method for analog circuits, drawing on the model-based and classifier-based fault diagnosis methods. The circle modeling method is a model-based fault diagnosis method and it can characterize all possible faults in an easy way for both soft faults and hard faults. And the ELM classification algorithm is not time consuming as a classifier. The circle model is used for feature extraction and the ELM classification algorithm is used as a fault classifier. The proposed method of circle model-based feature extraction and the ELM classification algorithm combination will fully inherit the completeness of the circle model and the fast classification of the ELM, and achieve higher accurate and efficient fault diagnosis of analog circuit.
# Image Processing and QR Code Application Method for Construction Safety Management
## 3 Image Processing-Based Worker Location Estimation System
### Image Processing Learning Model
#### 3.2.2 Target Object and QR Code Recognition  
An on-site surveillance camera is filmed from one direction. Unless it has a complex structure, a single device is installed in one space. In this study, the reference point of the object was determined by the worker's feet. Accordingly, the center point of the lower part of the object bounding box is assumed to be the floor position on which the worker is standing (Figure 6).  
Equation (6) represents the anchor box coordinates of the object, and Equation (7) represents the anchor box coordinates of the QR code. Both indicators form a rectangular shape made up of four points.  
\[\mathrm{A}=\left[\begin{array}{cc}x1,y1&x1,y2\\ x1,y2&x2,y2\end{array}\right]=\left[\mathrm{A},\;\mathrm{B},\;\mathrm{C},\; \mathrm{D}\right] \tag{6}\]  
\[\mathrm{QA}=\left[\begin{array}{cc}n1,m1&n1,m2\\ n1,m2&n2,m2\end{array}\right]=\left[\mathrm{E},\;\mathrm{F},\;\mathrm{G},\; \mathrm{H}\right] \tag{7}\]  
In this study, Equation (8) is applied to determine whether the QR code is included in the object.  
\[\left(\overset{\rightarrow}{\mathrm{AB}}\times\overset{\rightarrow}{\mathrm{ AE}}\right)\cdot\overset{\rightarrow}{k}=\left(\mathrm{B}x-\mathrm{A}x\right)\left( \mathrm{E}x-\mathrm{A}y\right)-\left(\mathrm{B}y-\mathrm{A}y\right)\left( \mathrm{E}x-\mathrm{A}x\right)\geq\;0 \tag{8}\]  
Equation (8) shows the method of calculating the outer product between the AB vector and the AE vector (Figure 7). If the result of the equation has a positive value, it means that the E point is located to the left of the AB line. As a result, if the coordinates (E, F, G, H) of the anchor box QA satisfies all these formulas for the anchor box A, it is proved that the QR code is inside the object.  
Figure 6: The reference position of the object recognized as an anchor box.
# Direct Fabrication of Ultrahydrophobic Laser-Induced Graphene for Strain Sensors
## 2 Materials and Methods
### Sensor Fabrication and Analysis  
LIG circuit was laser generated on top of the carbon fiber reinforced composite material (CFRP, 2.8 mm thick) to fabricate the strain sensor which had an insulating outer layer as received. Fast-drying silver paint ([PERSON], Redding, CA, USA) was used as the contact points which were connected to copper lead wires for four-probe measurements. Three-point bending tests were performed under flexure to characterize the strain sensing property of the fabricated LIG sensor. The mechanical sensing tests were performed at room temperature (22 \(\pm\) 1 \({}^{\circ}\)C) using a Zwick Roell Z100 machine with a load cell of 5 kN, rate of 0.5 mm min\({}^{-1}\), edge-to-edge spacing of 10 mm and maximum deformation of the loading nose at 1 mm. Throughout the bending test, the relative change in resistance was monitored synchronously using the four probe connections to the digital multimeter (Keithley DMM6500, Tektronix, OR, USA).