esa-sceva/satcom-chunk-collection huggingface dataset:
# Requirements Engineering for a Drone-Enabled Integrated Humanitarian Logistics Platform
## 5 Research Methodology
### Requirement Validation for the AIRDROP Platform
#### 5.2.4 Questionnaire Analysis
In this research, requirements with scores between 2 and 1 were assigned in this category. The ratings provided by the respondents serve as valuable inputs for the prioritization process, allowing for a comprehensive understanding of the relative importance and urgency of each requirement. The average score for each requirement was calculated, and then the MoSCoW technique was applied to categorize them into Must, Should, Could, and Would categories. This approach ensures that the most critical and essential requirements are identified and given the highest priority, while still considering the importance of other requirements. _Non-Parametric Tests_  
The Kruskal-Wallis H test for One-way Analysis of Variance (ANOVA) by Ranks is a rank-based nonparametric test that is used to determine statistically significant differences between groups of responders (for three of more groups) [95]. It is an omnibus statistical test and can only indicate that at least two groups are statistically different, without disclosing which ones [96]. In the present research, given the non-parametric nature of the data and the ordinal scale of response options ranging from 1 to 5, this test was used for multiple-group comparative inferential analysis, with a view to evaluating whether there were statistically significant differences in the respondents' perceptions of the importance of the requirements across their different professional backgrounds. The test enabled a thorough understanding of how their backgrounds may influence their perspectives and priorities in the context of the features and functionalities of the AIRDROP platform. A number of Mann-Whitney U tests were run as post hoc analyses in cases where significant differences existed among participant groupings, with the aim of identifying the specific groups where these differences are present. _Managing Participants' Uncertainty_  
In the dataset, responses denoted as \"Not Sure\" by participants were handled as missing values by SPSS during statistical analysis. Consequently, during the analytical process, these responses were excluded from the calculations pertaining to the corresponding requirements. By managing these responses as missing data, the acknowledgement of respondents' genuine lack of knowledge regarding certain requirements was ensured, thereby preventing any undue influence on our analysis. However, excluding \"Not Sure\" responses from the statistical analysis, while helping streamline our data processing, may have also limited our insight into areas of participant uncertainty regarding specific require ments. This decision was made with the aim of simplifying our analysis, but we recognize it as a deliberate trade-off rather than an oversight.
## 4 Results
### Monit4 Healthy Platform Development  
The Monit4 Healthy system continuously collects, processes, and visualizes real-time health data, permitting patients to monitor their vital signs, movement stability, and neuromuscular data through an interactive interface. Concomitantly, medical professionals can access detailed patient profiles to visualize historical data and analyze long-term health evolution, with the platform allowing clinicians to continuously monitor a patient and perform risk assessment. Automated alerts notify users of abnormal values or events, contributing to timely interventions.
# Analysis of the Development Status of eLoran Time Service System in China
## 6 Signal System
### Signal System Test  
According to the requirements of the high-precision ground-based time service system test, this article uses an eLoran signal simulator to conduct the compatibility testing of the ninth pulse modulation system signal with the existing receivers (UN152B).  
The simulator generates the ninth pulse system signal by overlaying it with the existing Eurofix system 0 us delay pulse or 151.875 us delay pulse. This is shown in Figures 11 and 12.  
Through experimental observation, as shown in Figure 13, it can be seen that eLoran receivers can operate normally, and receivers with a Eurofix demodulation function can continuously output and correctly demodulate the data. Based on the above experimental data, it can be basically determined that the eLoran simulator generates a ninth pulse system signal superimposed on the existing Eurofix system, which does not affect the normal operation and performance of the existing receiver.  
Figure 11: The 0 μs delay pulse.  
Figure 10: Ninth pulse modulation.  
This experiment can demonstrate that the signal system of the high-precision ground-based time service system of eLoran system is compatible with the existing eLoran receivers.
## 6 Simulation Results and Discussion
### Impact of Scan Parameters on Acquisition Performance  
Figure 15a illustrates the impact of selecting the overlap factor on acquisition performance. The overlap factor, which is directly related to the scanning step size \(n\), plays a crucial role in avoiding gaps during the scanning process. Specifically, a higher overlap factor reduces the risk of missing regions within the scanning area, which is essential for achieving high acquisition probabilities in the presence of jitter. Given the beam divergence, the pointing error deviation of the satellite due to vibrations, and the acquisition probability of 0.98 for this simulation, the necessary overlap factor can be calculated using Equation (78), and its relationship with the acquisition probability is shown in Figure 15a.  
As depicted, acquisition probability declines with an increase in \(\sigma_{\text{vib}}\), which represents the standard deviation of errors caused by satellite vibrations. This decline in acquisition probability can, however, be mitigated by increasing the overlap factor, effectively compensating for the increased positional uncertainty caused by vibrations. This result underscores the importance of adjusting the overlap factor based on expected error magnitudes to maintain optimal acquisition performance.  
Figure 15b shows a similar trend when the overlap factor is fixed and the beam divergence is varied. Here, the acquisition probability decreases as \(\sigma_{\text{vib}}\) increases, but this effect can be countered by increasing the beam divergence. Adjusting beam divergence is, thus, another viable approach to maintaining the acquisition probability when a fixed overlap factor is used.  
Overall, these findings suggest that optimizing the selection of both the overlap factor and beam divergence, particularly in scenarios with significant pointing and jitter errors induced by satellite platform vibrations, can minimize the need for multiple scans of uncertain areas and enhance the acquisition probability within a single scan. Proper selection of these parameters is crucial for robust performance in satellite-based scanning applications where uncertainty is a factor.  
Figure 15: Impact of scan parameters on acquisition probability in the presence of satellite pointing errors. (**a**) Impact of overlap factor on acquisition probability. (**b**) Impact of beam divergence on acquisition probability.
# Retention of Antioxidants from Dried Carrot Pomace in Wheat Bread
## 3 Results and Discussion
### The Influence of Carrot Pomace on Bread Properties
#### 3.3.3 Antiradical Properties of Bread
It should be stressed that polyphenols act as antioxidants in several directions: as reducing agents, substances that deactivate free radicals, chelate metals catalyze oxidation processes, activate antioxidant enzymes and deactivate oxidative enzymes, etc. [69; 70]. In food, all the above-mentioned ways of action of these compounds are encountered simultaneously. It can be concluded that the estimation of the antioxidant capacity of a given product is difficult, as it requires the use of multiple methods, based on different principles, taking into account the multiple roles of polyphenols as antioxidants. Also, the interpretation of the results of antioxidant activity determined by only one method is far from being sufficient and requires caution, especially in terms of health-promoting activity. It seems justified to analyze the antioxidant activity using several methods, which broadly define the antioxidant potential of raw materials, semi-products (carrot pomace) and products (CP bread). Thus, in order to evaluate the antioxidant potential of products in this work, we used methods that take advantage of the ability of antioxidants to deactivate stable free radicals (ABTS, DPPH) and to reduce metal ions to a lower oxidation state by the antioxidant under study (FRAP, FOMO) [71; 72]. These methods are complimentary, because the FRAP method covers most antioxidant components in the sample, while the DPPH method detects only some of the most reactive ones, and the ABTS method gives intermediate values [71]. In addition, other substances, such as macromolecular Maillard reaction products formed at high temperatures during baking, which also exhibit antioxidant properties, may have contributed to the antioxidant capacity discussed above [60]. Summarizing, the bread obtained in the study was characterized by a high content of health-promoting compounds compared to the control; nevertheless, its sensory characteristics (intensive color and carrot smell) could not be accepted for the commercial product. Since the dough used for baking is characterized by acceptable technological propertiesand the baking process itself runs smoothly, it will be possible to use the baking process to prepare a semi-finished product--breadcrumbs, suitable for coating and thickening applications, especially for ernobing of meat products. Such an ingredient, apart from its favorable nutritional composition, would be characterized by intense and desirable color and acceptable taste, with no change in processing technology in comparison to standard bread. The latter is especially important because of the significant influence of physical characteristics of breadcrumb coating on consumer acceptance [73]. Additionally, the use of such breading systems would broaden the range of natural antioxidants applicable for meat products [74].
# TRUST-ME: Trust-Based Resource Allocation and Server Selection in Multi-Access Edge Computing
## 5 Numerical Evaluation
### Scalability Analysis  
As discussed in this section, we analyzed the scalability of the proposed TRUST-ME model by varying the number of MEC servers and users. Figure 6a-c show the average computing capacity allocated to each user, the corresponding experienced average user's utility, and the resulting average latency experienced as the number of MEC servers and users changed. The results reveal that as the number of users increased and the number of MEC servers remained constant, the average computing capacity available to each user decreased, and thus, this caused an increased latency. This phenomenon occurred due to the finite computing capacity of the MEC servers, which when divided between more users, led to greater utilization of the MEC servers' resources, and thus, ultimately increased the users' experienced latency.
## 1 Introduction
### EDX Analysis of Silicon Contamination  
The contaminants from the dicing process can be analyzed by energy-dispersive X-ray spectroscopy (EDX) analysis (shown to include Si, Cu, N, and O elements), which may include not only solid elements or chips from the diamond blade but also adhesive residues from UV glue of tape or base film (Figure 1). The EDX analysis explains why it is difficult to remove these contaminants, especially those in Level 1, where fine powder of silicon is deposited around the bumps, shielding them from cleaning agents by shadow effect.  
Figure 1: EDX analysis of silicon contamination finding elements of Si, N, O, and Cu, all mixed with other residues from the dicing blade, taping, glue, etc.  
\begin{table}
\begin{tabular}{c c|c|c|c} \hline \hline
**Level 1** & **Level 2** & **Level 3** \\ \hline Circular around bumps & \multicolumn{2}{c}{Deposit at non-bump area} & Water mark \\ \hline \hline \end{tabular}
\end{table}
Table 1: Three levels of silicon contamination.
# Multidisciplinary Study of Mud Emissions Following the 2016 Norcia Earthquake
## 3 Methodology
### Mud Chemical Analysis  
The mud geochemical analysis was carried out after air-drying, sifting (<2 mm), and quartering to obtain a representative sediment volume (about 200 gr). Soil chemical analysis followed the standard analytical procedure endorsed by the Italian Ministry of Agriculture (D.M. 13 September 1999 that ended on 25 March 2002). The mud conductivity and the pH were determined by an aqueous phase analysis after appropriate mixing with milliQ water. Mud acidity was measured either in water (pH\({}_{\text{w}}\)) or in calcium chloride (pH\({}_{\text{Ca}}\)). The pH\({}_{\text{Ca}}\) is considered the more accurate of the pH measured on the water as it reflects what the plant experiences in the sediment. The values of pH\({}_{\text{Ca}}\) are usually lower than pH\({}_{\text{w}}\) by 0.5 to 0.9 following a nonlinear relationship. The pH\({}_{\text{Ca}}\) was determined on a solution suspension of sediment-CaCl\({}_{2}\) (0.1%) (1:2.5 ratio). The electrical conductivity was measured on a filtered (2.5 \(\upmu\)m) aqueous extract of mud (1:2 sediment-water ratio) equilibrated overnight.  
Major elements were determined on filtered (2.5 \(\upmu\)m) aqueous extract of mud (1:5 sediment-water ratio). The alkalinity (HCO\({}_{3}\)\({}^{-}\) and CO\({}_{3}\)\({}^{2-}\)) was not directly quantified by titration with 0.05 N HCl due to the turbidity of the samples. It was computed for difference among major anions and cations by assuming a maximum analytical error of 5%. Major elements were analyzed in the laboratory using chromatography systems (Dionex-Thermo ICS 1100) in suppressed mode, equipped with an anion column (AS14A) and a precolumn (AG14A) that works under a continuous flow of the carbonate-bicarbonate eluent for anions (F\({}^{-}\), Cl\({}^{-}\), Br\({}^{-}\), NO\({}_{3}\)\({}^{-}\), and SO\({}_{4}\)\({}^{2-}\)) and a cation column (CS12A) and pre-column (CG12A) that works under a continuous flow of methanesulfonic acid for cations (Na\({}^{+}\), K\({}^{+}\), Mg\({}^{2+}\), and Ca\({}^{2+}\)); the precision and accuracy of the method are described in [49]. Major anions and cations were determined on filtered (0.45 \(\upmu\)m) and filtered and acidified (HCL 6M) samples, respectively. Chemical-physical parameters and major element chemistry of the sampled sediments are reported in Table 2.
# Application of Single-Electron Transistor to Biomolecule and Ion Sensors
## 6 Summary and Future Perspectives
One significant problem in achieving the integration of ultrahigh-sensitive SET sensors is that it is difficult to obtain the uniform \(I_{d}\)-\(V_{g}\) characteristics for the plural SETs, although room-temperature SET operation can be possible. Since the island size has to be on the order of 10 nm, simply by adopting the multiple-island channel structure for room-temperature SET operation, a size fluctuation of only a few nm leads to quite different \(I_{d}\)-\(V_{g}\) characteristics for the SET, which will make it difficult to integrate the sensors. More precise control of the size of the channel structure is necessary by refining the EB lithography or dry etching technique, although it would be very difficult to avoid the problem of line edge roughness for thin and long Si wire structures. A combination of the EB lithography technique and the self-limiting or assembling technique is another possible way to obtain reliable room-temperature SET operation. For example, [PERSON] _et al._ reported the room-temperature operation of an SET with a Coulomb island less than 5 nm in size that was fabricated by combining the EB lithography with the pattern-dependent oxidation of Si nanowire [34]. By overcoming such problems, Si SET biosensors will open the door to an integrated single-chip sensor system suitable for multiplexed and simultaneous diagnoses with ultrahigh sensitivity. This study was supported in part by a Grant-Aid for Scientific Research (B) (Grant No. 25289103) from Japan Society for the Promotion of Science. The author declares no conflict of interest.
# Intersection and Complement Set (IACS) Method to Reduce Redundant Node in Mobile WSN Localization
## 4 Proposed Method
### Simulation Experimental Setup  
The performance of MSL*, LCC and IACS are compared and evaluated with identical experimental settings in Section 3 (Table 1) and true node locations. Since the environment occurs on a flat surface, the coordinate is in \((x,y)\). RSSI is applied according to Reference [19] to derive the Euclidean distance \(d\), between the pair of nodes that overlap.  
Each node is assumed to have a perfect circle radio range, \(r\), for transmission and their distance with other nodes are known. All three localization methods are assumed to run simultaneously using the same true location. The node density (Nd) is the average density of all sensor nodes in the tested environment, while the seed density (Sd) is the average density of the seed nodes. The simulation is executed for 50 iterations (200-time slot in each iteration), where the estimated node locations and their true location are reset after each iteration to compare the average accuracy over time between the methods. In each time slot, each node speed varies from 0 to \(maxv\) and moves in different directions. The nodes are assumed to move according to the modified random waypoint model [20] where the pause time is set to 0 [21]. The mobility reduces the dependency on neighbor nodes with known location. Despite the number of seed numbers deployed in the network, the number of the localized node increases in each time slot as long there is a seed node in the whole network. Each node changes places in each time slot to open the opportunity to gain new samples from their new neighbors. Therefore, nodes in the network localize faster if more seed nodes are initialized.
# Analyzing the Effect of Negation in Sentiment Polarity of Facebook Dialectal Arabic Text
## 2 Background  
### Naive Bayes-Based Approach  
The previous work [12] that this study is based on compares and contracts the machine learning approach, Naive Bayes, against the lexicon-based approach in classifying the sentiments of Facebook posts. The classification was done in five categories: positive, negative, dual (either positive or negative), neutral, and spam. In this approach, the authors assume that expression opinions using phrases has limitations and depends on the dialect. For example, condolence can be expressed by one verse from Qur'an. Sarcasm can be expressed by phrases taken from famous plays. Thus, to extract patterns from the corpus, manual tagging was used. The phrases used for tagging each post consist of one or two words that determine the polarity of the post. The corpus used in this work consists of posts that discuss politics, social events, and sports. The posts were written in informal Arabic language with the following dialects: Lebanese, Syrian, Iraqi, Egyptian, Libyan, Tunisian, Algerian, Saudi, and Sudanese. The classification was done using the Naive Bayes probabilistic classifier that assumes that the features used for classification are independent. This classifier was used in two setups: The first setup uses a vector holding the following features: Positive phrase, negative phrase, positive emoticon, negative emoticon, spam, and manual tag. The manual tag can be positive, negative neutral, dual, or spam. The second setup uses a vector holding the following features: Positive phrase, negative phrase, positive emoticon, negative emoticon, and subjectivity. Subjectivity is a Boolean value that identifies whether the post is subjective or objective. The common fields in both vectors are Boolean values to indicate the presence or absence of a feature. The performance measure of setup one was 85.61%, whereas in setup two it was 75.17%.
# Assessment of the Length and Depth of Delamination-Type Defects Using Ultrasonic Guided Waves
## 4 Verification of Proposed Delamination Depth and Length Estimation Technique  
### Verification with 2D Model  
To demonstrate the overall performance of the proposed delamination depth and length estimation method, two separate 2D GFRP finite element models, both with dimensions of 2000 mm \(\times\) 4 mm shall be considered. For the sake of better understanding, let us denote them as sample No. 1 and sample No. 2. Each of the considered models contains delaminations of different sizes and through-thickness locations. In sample No. 1, the delamination with a length of \(x_{1}\) = 70 mm is introduced 1 mm below the top surface (\(h_{11}\) = 1 mm, \(h_{21}\) = 3 mm). Meanwhile, sample No. 2 has a defect of \(x_{2}\) = 90 mm located at a depth of 1.5 mm (\(h_{12}\) = 1.5 mm, \(h_{22}\) = 2.5 mm). A sketch of the considered cases is presented in Figure 12.  
Throughout the simulations, 2D structural solid plane-42 finite elements were used. The same properties of GFRP laminate were maintained as described in the previous section. In each of the investigated cases, a Gaussian envelope tone burst of three cycles was used for excitation. The excitation frequencies were changed within the range from \(f_{1}\) = 50 kHz to \(f_{\rm n}\) = 200 kHz with increments of 10 kHz. Hence, 16 different excitation frequencies were used for each of the two considered models. The spatial size of the element in all cases was constant and equal to 0.5 mm, which corresponds to  
Figure 11: Magnitude variation of A\({}_{0}\) mode due to the size of defect at fixed depth: comparison between analytical calculations and experiment.  
Figure 12: Graphic representation of investigated cases: sample No. 1 with 70 mm wide delamination located 1 mm below the surface (**a**), sample No. 2 with delamination of 90 mm at depth of 1.5 mm (**b**).  
12 up to 37 nodes per wavelength for the slowest A\({}_{0}\) in a frequency range of \(f_{1},f_{2},\ldots,f_{\rm n}\). A\({}_{0}\) mode was introduced into the structure by applying the out-of-plane nodal displacements to the edge of the sample in the same way as it was demonstrated in Figure 8. The integration step in the time domain varied from 1 \(\upmu\)s for the lowest excitation frequency \(f_{1}=50\) kHz to 0.25 \(\upmu\)s for \(f_{\rm n}=200\) kHz. The variable monitored in this study was a vertical component of the particle velocity (\(y\)) at nodal locations \(r_{1}\) (\(x_{1}=750\) mm, \(y_{1}=4\) mm) and \(r_{2}\) (\(x_{2}=1250\) mm, \(y_{2}=4\) mm).