esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Overall Design and System Analysis
### System Implementation
#### 4.3.2 Integrated Signal Design  
For the underwater CPNT system, each service is performed by acoustic communication. However, the separated realization, which is the current practice, will increase the strain on limited energy and communications resources. To conduct the integrated CPNT service, the key point is to implement the signal structure with the communication and positioning fusion design. With the positioning signal embedded, long baseline acoustic positioning technology can be enhanced. With the application of multi-user reliable  
Figure 4: \(U^{2}CPNT\) system framework which consists of underwater systems, buoy positioning base station, positioning calculation system, display control system and network system.  
Figure 3: Minimum \(U^{2}CPNT\) system with 1 floating buoy, 4 subsurface buoys and 1 manned surface boat, providing CPNT service for underwater vehicles using acoustic signals, which presented by dotted arrows.  
transmission networking technology, the fusion of underwater acoustic communication, positioning, and networking can be achieved.  
We take OFDM as the basic communication model, whose data rate is higher. Typically, a integrated \(U^{2}CPNT\) signal structure is shown in Figure 5.  
There are three components in the signal: dual-HFM, time slots, and CP/ZP-OFDM. Each part of the frame serves for positioning and communication, whose function is described in Table 2.  
From the point of view of system optimization, the advantages of integrating communication, positioning, and networking are capable of enhancing acoustic compatibility, reducing costs, minimizing size and power usage, increasing bandwidth efficiency, and strengthening information transmission and equipment control capabilities.
# Hybrid Trust Model for Node-Centric Misbehavior Detection in Dynamic Behavior-Homogeneous Clusters
## 7 Collaborative Node-Centric Misbehavior Detection Based on Hybrid Trust Values
### Cluster Head Layer Misbehavior Detection  
The cluster head vehicle \(C_{i}\) calculates the trust threshold \(T_{thresh}^{C_{i}}(v_{i})\) based on the average total trust value \(T_{totm}(v_{i})\) of vehicle \(v_{i}\), using this threshold to determine the vehicle's status and report malicious vehicles to the cloud management module. The formula for calculating the threshold \(T_{thresh}^{C_{i}}(v_{i})\) is as follows:  
\[T_{thresh}^{C_{i}}(v_{i})=\frac{\sum_{j=1}^{n}T_{totm}(v_{i})}{n} \tag{27}\]  
The process of cluster head vehicle \(C_{i}\) making a determination about vehicle \(v_{i}\) by using \(T_{thresh}^{C_{i}}(v_{i})\) is as follows:  
\[\left\{\begin{array}{ll}T_{totm}(v_{i})>T_{thresh}^{C_{i}}(v_{i}),&\;\;\;\; \;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\; \;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\; \;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\; \;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\; \;\;\;\;\;
# An Ontology-Driven Learning Assessment Using the Script Concordance Test
## 1 Introduction
MCQs are generated using ontologies, and the assessment is made based on the answers obtained from the attending candidates. Their results show that, although the system they proposed is very simple, it provides a better percentage of correct answers than the existing optimization algorithms [34]. A bilingual ontology-based automatic question generation system was proposed by [PERSON], [PERSON], and [PERSON] [35]. It is designed to help learners to generate questions for self-evaluation on laboratory materials concerning product and security rules. MCQ and true/false questions are generated on the fly and distracters change in each execution, providing for the same question a different content. Classes, properties, and individuals are used as inputs to generate questions. The authors also developed a web application that has a user-friendly interface to generate questions on products and materials used in lab works. In the backend is an information querying module that uses SPARQL to query data from ontology [35]. A modular system called the EEMMeT multiple-choice question generator (EMCQG) was introduced by [PERSON] et al. [36]. EMCQG is based on The Elsevier Merged Medical Taxonomy (EMMeT) database. It generates medical MCQ questions whose stem is in the form of patient vignettes. This type of question is standard in medical education because of its ability to evaluate clinical reasoning. However, EMCQG is not open source and, thus, not available for public review [36]. In our previous study [37], we developed an ontology called SCTonto, with the goal of automated question generation for the SCT assessment method. SCTonto proved suitable for the purpose. However, a methodology for the development of an ontology-based platform for learning assessment based on SCT was not considered. The main contributions of this paper are the following:  
* A methodology for an ontology-driven learning assessment is proposed and proven in the case of script concordance tests;
* SCTonto ontology, developed in our previous study, is enhanced and confirmed usable in the context of the presented methodology;
* A novel ontology-driven automated script-concordance-test-based assessment platform is proposed;* The proposed platform is evaluated against the traditional manually created SCT;
* Presented experimental results indicate the significant reduction in tests creation time, confirming significant improvements in scalability. The remainder of the paper is structured as follows: Section 2 presents the core of this paper with a detailed structure of ontology-driven framework for automated SCT question generation. Section 3 gives results of the evaluation of the traditional construction of SCT against the ontology-based question generation. Discussion about obtained results is given in Section 4. Finally, Section 5 summarizes the main ideas of this paper and outlines the following technical steps in the evaluation of our approach.
# An EMD-SARIMA-Based Modeling Approach for Air Traffic Forecasting
## 1 Introduction
### Objective of Paper  
Considering that there is still much study that is required to be done in air traffic forecasting, and that the hybrid theory-based model may have better performance in prediction issues according to those modeling approaches which have already been done, in this paper, the first effort to forecast the air traffic of China's civil aviation is attempted with the aid of empirical mode decomposition (EMD) and seasonal autoregressive integrated moving average (SARIMA). To be specific, EMD has its advantage in data analysis, and is highly adaptive, efficient, capable of dealing with nonlinear, non-stationary processes, and preserving the physical meanings of the original data [13], for the basis function in EMD can be directly derived from the data input; while autoregressive integrated moving average (ARIMA) is an integrated version of autoregressive moving average (ARMA), has a more accurate performance in short-term forecasting within time series models [14], and SARIMA can even capture the periodicity that is typical for the air passenger flow data process. Therefore, the hybrid modeling approach based on EMD-SARIMA proposed in this paper is supposed to solve the specific problems which might appear in air traffic forecasting. Moreover, a horizontal performance comparison of several hybrid theory-based forecasting models has also been made in this paper by referencing the cargo and passenger flow data from the years 2006 to 2014 available at the official website of the Civil Aviation Administration of China (CAAC). Thus, the problem of the most suitable modeling approach for short-term air traffic forecasting has been solved on one hand, and the advantage of the EMD-SARIMA-based model has been demonstrated on the other hand.
## 4 Results and Discussion
These modern software tools are already available on the market; it is strongly recommended to use the latest available software in all the path-measuring optimizations. Full maintenance for software can be expensive, but it will certainly be compensated within a reasonable time period. In brief, this is what we can call an intelligent CMM. CMM inspection shall be performed even 3-6 times on a part during the manufacturing processes. The first inspection is on the casting, the second one on the coated surfaces, and the third inspection after any heat treatment, to check for thermal deformations. The fourth inspection should be during or after all the machining operations. At this point, there is still a possibility to implement a repair method and perform a re-staggering action to rotate the airfoil in relation to the machined facets which interface with other components. A fifth inspection can be performed after any extra operations involving any kind of heating, like welding or brazing of plates and tubes, where the whole product is put into a furnace. The last inspection is performed at the arrangement level to provide an average flow rate through the complete ring assembly. It is recommended to use at least three CMM inspections: for the cast part, after the heat treatment, and before the final assembly on the final product. Simplifying measurements, which are performed during each inspection,  
Figure 12: Average distance error between 10 and 1000 control points based on real CMM measurements for a part with defect. significantly reduces the time required for each inspection, therefore optimizing the overall manufacturing process. The time saved due to simplified measurements is easily transferable to the overall part cost, which is highly sought after in view of current world industry competitiveness. In Figure 13 a report example is presented. From an engineering perspective, short and well-presented information about deviations is preferable in order to approve the developed parts. When all measurements meet our expectations (the values in the figure are in green) and the measured spline is within the tolerance zone, the part can be approved automatically. Red or yellow (black in this article -- to improve contrast and readability) colors are used to indicate errors and then the part can be approved if these errors do not occur in critical places. These reports are very easy to review, as they usually contain hundreds of sections for all parts in an ordered set. Twenty-five points, as used in this case, is a good compromise between speed and accuracy. The part can still be accepted based on an engineering analysis with a simplified inspection. There is no reason to scrap parts with small flaws, but those parts should be carefully verified and accepted separately piece by piece. There are many possible scenarios for fixing the shape, such as additional machining, welding, and grinding if the identified flaw is too serious.
## 6 Numerical Experiments
### Results and Discussion
The optimal solution obtained by PSACO algorithm is, \(s_{1,13}\)\(s_{2,6}\)\(s_{3,14}\)\(s_{4,4}\)\(s_{5,1}\)\(s_{6,1}\)\(s_{7,14}\)\(s_{8,5}\)\(s_{9,10}\)\(s_{10,3}\) with the objective function value of 1.4432, comparing with the results of \(s_{1,13}\)\(s_{2,6}\)\(s_{3,14}\)\(s_{4,4}\)\(s_{5,6}\)\(s_{6,1}\)\(s_{7,14}\)\(s_{8,5}\)\(s_{9,10}\)\(s_{10,2}\) with 1.4844 and \(s_{1,10}\)\(s_{2,12}\)\(s_{3,A}\)\(s_{4,A}\)\(s_{5,1}\)\(s_{6,1}\)\(s_{7,15}\)\(s_{8,5}\)\(s_{9,11}\)\(s_{10,2}\) with 1.6588 by PSO and ACO, respectively. Apparently the optimal supplier integration result from PSACO exceeds that of PSO and ACO in terms of the objective function values. We extend the three solutions and find their event values on the four indices for each of them. Firstly, the total cost of the supply chain obtained from each algorithm is 124 on PSACO, 135.2 on PSO, and 135.6 on ACO, showing a 9.03% saving of PSACO over PSO, and 9.35% saving of PSACO over ACO. Optimizing supply chain costs at a competitive service level can greatly improve the profitability. Secondly, the trustworthiness values of the supply chains are 785.45, 683.85 and 763.11 for PSACO, PSO and ACO respectively, showing that the solution from PSACO has great advantage in improving the trust relationship among the supply chain partners. In collaborative innovation of the supply chain, trust is the foundation of building tight alliances and can greatly reduce the cooperative risk. Thirdly, the values of overall supplier chain service are 974, 971, and 975, in which PSACO is the second best. Having a high level of modularization structure of the supply chain in order fulfilment will ensure that products het to market in a fast and efficient way with the most consistent levels of fulfilment precision. Finally, the qualified product rates are 80%, 78%, and 80%, indicating that PSACO has a fine ratio. A successful supply chain system should be modelled in detail by a programming approach that takes into account not only downgraded products but also the customer requirements for the quality qualification rate to maximize the total profit of the product portfolio. In the overall performance of the key measurements, the supply chain partnership selected by PSACO creates the integration or tight process and information linkages between function across the supply which allows the smooth, synchronized flow of both information and product between customers, suppliers and logistics providers.
# A Miniaturized and Fast System for Thin Film Thickness Measurement
## 5 Experiments and Discussion
### Measurement Experiment of PCB Chip Film Thickness  
To protect the key chips on semiconductor PCB, the surface is generally treated with coating or glue. The coating thickness is various in a different area, thus fast and non-destructive measurement has important engineering value. This paper aims at the needs of industrial PCB chip transparent film thickness measurement and uses the method to carry out experimental verification. For different areas of the PCB board, the transparent film with 1-30 thickness is measured multiple times. In Figure 12, the measurement results at three points a, b, and c on the different electronic chips are 2.067,, 3.51, and 24.91, respectively, which match the reference values 2,, and 25 provided by the factory. The absolute thickness errors are 67, 15, and 90, respectively.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Methods** & \multicolumn{2}{c}{**PPS**} & \multicolumn{2}{c}{**WLI**} \\ \hline
**Number** & **Thickness (\(\mu\)m)** & **Deviation (\(\mu\)m)** & **Thickness (\(\mu\)m)** & **Deviation (\(\mu\)m)** \\ \hline
1 & 0.916 & \(-\)0.084 & 0.835 & \(-\)0.165 \\
2 & 0.839 & \(-\)0.161 & 0.901 & \(-\)0.099 \\
3 & 0.763 & \(-\)0.237 & 0.913 & \(-\)0.087 \\
4 & 0.992 & \(-\)0.008 & 1.030 & 0.030 \\
5 & 0.763 & \(-\)0.237 & 0.939 & \(-\)0.061 \\
6 & 0.916 & \(-\)0.084 & 0.942 & \(-\)0.058 \\
7 & 0.916 & \(-\)0.084 & 0.968 & \(-\)0.032 \\
8 & 0.916 & \(-\)0.084 & 0.989 & \(-\)0.011 \\
9 & 0.839 & \(-\)0.161 & 1.010 & 0.010 \\
10 & 0.839 & \(-\)0.161 & 0.972 & \(-\)0.028 \\
11 & 0.916 & \(-\)0.084 & 0.998 & \(-\)0.002 \\
12 & 0.992 & \(-\)0.008 & 0.955 & \(-\)0.045 \\
**Mean** & **0.892** & & **0.954** \\
**Standard** & **0.076** & & **0.053** \\
**Deviation** & **0.076** & & **0.053** \\ \hline \hline \end{tabular}
\end{table}
Table 1: PPS and white light interference (WLI) measurement results of germanium-based 1 and standard film.  
Figure 11: (a) The SiO\({}_{2}\) film with a 1 step on the germanium substrate. (b) The three dimensional morphology of step by white light interferometry.
# Reinforcement Learning of Bipedal Walking Using a Simple Reference Motion
## 3 Proposed Method
### State  
The state \(s_{t}\) consists of the observations obtained from the environment in the most recent five steps \(\{o_{t}\), \(o_{t-1}\), \(o_{t-2}\), \(o_{t-3}\), \(o_{t-4}\}\) and also of a phase vector (Figure 1).  
The observation \(o_{t}\) at each time step is a 16-dimensional vector consisting of the 10 joint angles of the robot's legs and the 3-dimensional linear acceleration and 3-dimensional angular velocity of the robot's torso. Thus, the five observations \(\{o_{t}\), \(o_{t-1}\), \(o_{t-2}\), \(o_{t-3}\), \(o_{t-4}\}\) are represented by an 80-dimensional vector. The reason for using the past observations from \(o_{t-1}\) to \(o_{t-4}\) is to provide the policy with more information to infer the dynamics of the environment [28].  
The phase vector is a 2-dimensional vector consisting of \(\{\sin(\frac{2\pi t}{T}),\,\cos(\frac{2\pi t}{T})\}\), where \(T\) is the period of the walking motion to be learned and \(t\) is the time step since the start of the episode. It is known that learning may be facilitated by providing such a phase vector, since walking is a cyclic movement [29].  
In total, the state \(s_{t}\) is an 82-dimensional vector. It is input to the neural network (Figure 1).
# Burst Channel Error Reduction Based on Interleaving for Efficient High-Speed Wireless Communication
## 5 Simulation Results  
The experiments in this section have been carried out using the MATLAB 7.5 program. Experiments have been conducted on an i5-2.3 GHz laptop running Microsoft Windows 7. In this section, computer simulations are presented to examine and evaluate the BER performances of different scenarios.  
1. Different wavelet families are used in DWT- and FFT-OFDM.
2. Over the AWGN channel model, the proposed systems are compared to conventional (FFT/DWT)-OFDM systems.
3. With an exponential power delay profile Rayleigh fading channel without a Doppler effect, the proposed systems are compared to conventional (FFT/DWT)-OFDM systems.
4. In the presence of AWGN, the suggested systems are compared to conventional (FFT/DWT)-OFDM systems.
5. The suggested systems are compared to traditional (FFT/DWT)-OFDM systems over the AWGN outdoor channel.  
To ensure the success of the proposed systems, we introduce the BER versus \(E_{b}\)/\(N_{0}\) for all systems, where \(E_{b}\) is the energy per bit and \(N_{0}\) is the noise power spectral density. The number of sub-carriers considered equals 512, with each sub-carrier having 16 symbols. The guard interval length is one-eighth of the symbol duration. QPSK or 4-QAM (\(M=4\)) data symbols are used in the simulation experiments. In all later experiments except in the following subsection, we use the value of \(S=5\), where the evaluation results show that this value is the best for all experiments. Table 2 summarizes the simulation parameters.
## 3 Results  
The ability to recover bioactive molecules of two extraction techniques, one with cold water (20 \({}^{\circ}\)C), the other with hot water (95 \({}^{\circ}\)C), from the pericarp of different accessions and varieties of chestnut was investigated. It has been demonstrated that, at the same extraction time, hot water is a more effective extractant [19]. So, in this work, the contact time between matrix and solvent was diversified: 4 h with cold water and 1 h with hot water. The results of this experimental plan are reported in Tables 2 and 3, where it has been shown that the two extraction techniques sometimes lead to the same result, and other times to significant and even important quantitative and qualitative differences.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{\
\begin{tabular}{c} **Accessions** \\ **or Variety** \\ \end{tabular} } & \multirow{2}{*}{
\begin{tabular}{c} **T \({}^{\circ}\)C** \\ **(mg GAE g\({}^{-1}\) DM)** \\ \end{tabular} } & \multicolumn{2}{c}{**Total Phenolics**} & \multicolumn{2}{c}{**Total Flavonoids**} & \multicolumn{2}{c}{**Proanthocyanidins**} \\ \cline{3-6}  & & \multicolumn{2}{c}{**F-C**} & \multicolumn{2}{c}{**CV**} & \multicolumn{2}{c}{**mg CE g\({}^{-1}\) DM**} & \multicolumn{2}{c}{**mg CE g\({}^{-1}\) DM**} \\ \hline \multirow{3}{*}{**MURG**} & 20 & 39.58 \(\pm\) 1.69 & 6.79 \(\pm\) 0.25 \({}^{\ast}\) & 18.69 \(\pm\) 0.42 \({}^{\ast}\) & 9.10 \(\pm\) 0.72 \\  & 95 & 37.35 \(\pm\) 0.64 & 4.92 \(\pm\) 0.18 \({}^{\ast}\) & 16.52 \(\pm\) 0.14 \({}^{\ast}\) & 9.20 \(\pm\) 0.20 \\  & 20 & 44.33 \(\pm\) 2.89 & 6.44 \(\pm\) 0.11 & 12.92 \(\pm\) 1.70 \({}^{\ast}\) & 6.37 \(\pm\) 1.17 \\  & 95 & 40.10 \(\pm\) 2.16 & 7.37 \(\pm\) 0.39 & 16.44 \(\pm\) 2.3 \({}^{\ast}\) & 7.55 \(\pm\) 1.38 \\  & 20 & 42.96 \(\pm\) 1.25 & 7.82 \(\pm\) 0.25 & 11.37 \(\pm\) 1.14 \({}^{\ast}\) & 7.05 \(\pm\) 1.25 \\  & 95 & 38.92 \(\pm\) 2.89 & 7.48 \(\pm\) 0.33 & 16.26 \(\pm\) 1.62 \({}^{\ast}\) & 7.99 \(\pm\) 0.96 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Total phenolics (TP) assessed by Folin-Ciocalteu (F-C) and cyclic voltammetry (CV) at +0.8 V, total flavonoids (TF) and proanthocyanidins (PA) in the extracts of the pericarp chestnut samples.
## 3 Results and Discussion
### Pulsed Electric Fields (PEF)-Assisted Extraction
#### 3.2.2 Dimethyl Sulfoxide/Water  
Figure 7 shows the results obtained for chlorophyll, carotenoids, TPC, TEAC, and ORAC content after conventional and PEF-assisted extraction using DMSO/H\({}_{2}\)O as a solvent. After performing a two-way ANOVA (time and treatment), it was observed that both extraction time and treatment had a significant effect (\(p<0.05\)) on the extraction of chlorophylls, carotenoids (Figure 7a), and TPC (Figure 7b). This effect was less than that observed after using the EtOH/H\({}_{2}\)O mixture, mainly due to a lower solvent extraction capacity, as could be observed after using the conventional extraction method (Figures 3 and 4).  
Lower TEAC values were also observed due to a decreased extraction of antioxidant compounds (chlorophylls, carotenoids, and phenolic compounds) (Table 1). However, the ORAC values were not significantly affected, although a non-significant increase was found when longer extraction times were used.  
Figure 6: Chlorophyll a, chlorophyll b, and carotenoid content (**a**); TPC, TEAC, and ORAC (**b**) after conventional extraction and PEF-assisted extraction with EtOH/H\({}_{2}\)O. Different lower-case letters in the same parameter indicate statistical differences depending on the extraction time or treatment used.  
It should be noted that the maximum extraction of chlorophyll a and chlorophyll b occurred 15 min after applying the PEF pre-treatment, with values of 0.39 \(\pm\) 0.01 mg/g DM and 0.32 \(\pm\) 0.01 mg/g DM, respectively. However, after applying the conventional treatment, these values were not obtained until 180 min. PEF pre-treatment reduced the extraction time by 165 min. Regarding carotenoids, a similar effect was found, with the maximum carotenoid extraction (0.15 \(\pm\) 0.01 mg/g DM) observed after applying the PEF pre-treatment and subsequent extraction for 15 min, obtaining lower values (0.08 \(\pm\) 0.00 mg/g DM) than after using conventional extraction for 180 min.  
The TPC content was also increased by PEF pre-treatment, for example, the maximum content extracted at 5 min after PEF pre-treatment (12.53 \(\pm\) 0.31 mg AGE/g DM) was much higher than that obtained at 180 min after conventional treatment (4.84 \(\pm\) 0.48 mg AGE/g DM).