esa-sceva/satcom-chunk-collection huggingface dataset:
# Extraction of Visible Boundaries for Cadastral Mapping Based on UAV Imagery
## 4 Discussion
### Applicability of the Developed Workflow  
The developed workflow provided geo-referenced boundary maps in a format compliant with the formats that are used in GIS environments. This shows that the extracted objects can be easily transferable, and applicable in GIS for cadastral purposes. In cases where cadastral maps are rarely present and the concept of fit-for-purpose cadastre is in place, the workflow, with the selected method for automatic extraction of visible boundaries, shows the potential for the automation of the visible cadastral boundary delineation procedure [1]. Thus, the approach developed generally contributes to the acceleration and facilitation of the creation of cadastral maps (Figure 9b), especially in developing countries, where general boundaries are accepted, and positional accuracy is of lesser importance [25]. However, the approach is suitable for the areas where the boundaries of physical objects are visibly detectable on a UAV orthoimage, for instance, in rural areas. The workflow might be applicable for both the creation and updating/revision of cadastral maps, similar to the manual delineations of cadastral boundaries on a UAV orthoimage. In addition, the workflow developed might lower the costs and time compared to the manual delineation of cadastral boundaries, especially in rural areas [26].  
Furthermore, in developed countries, the approach based on automatic extraction of visible boundaries might be used for a revision of current cadastral maps (Figure 9a). In this case, the extracted visible boundaries can be used as a basis for a new cadastral survey or land rearrangements, depending on the discrepancy between cadastral maps and land possession (as shown in the case study). Although the beneficiaries agree with the visible boundaries, if higher accuracy is required, the revised objects (spatial units) can later be manually delineated from a UAV orthoimage or re-surveyed with ground-based surveying techniques. It must be emphasized that the extracted visible boundaries, both for the creation of cadastral maps and updating, should be inspected by the local community and all beneficiaries (landowners, other land rights holders) in order to be legally validated.
## 6 Synthetic Scaffolds
### Calcium Phosphates  
Calcium-based bone substitutes are a particularly large group of materials used in bone tissue engineering [35]. These include calcium sulfates, tricalcium phosphate (TCP), hydroxyapatite (HA) and biphasic calcium phosphates (TCP + HA). Unlike natural scaffolds and synthetic polymers, the chemical and operation properties of calcium products are similar to the mineral phase of bone [63]. The high mechanical stiffness (Young's modulus), hardness, brittleness and low elasticity make calcium substitutes appropriate for bone regeneration [63]. Compared with human bone, the compressive strength of calcium phosphates is generally much higher, though they have a lower tensile strength, fracture toughness and increased fragility [63; 64]. Calcium-based scaffolds are also biocompatible, osteoconductive and bioactive, meaning that they are capable of forming a biological interface with host tissue [65]. This can help to prevent implant dislocation. However, it has been postulated that the dissolution of calcium sulfate, like other synthetics, leads to an acidic microenvironment which may cause inflammation [66]. There is also evidence to suggest that some products which are marketed as being resorbable, may still persist over several years in some patients [67]. This is not ideal as the defect should be replaced by new, stronger bone in all cases.  
The potential of antibiotic-eluting, biodegradable, calcium-based scaffolds in chronic osteomyelitisitis has been long recognised [68]. As a result, there is a wealth of literature in this area. Importantly, this has led to numerous clinical trials with positive results (Table 1). It has also inspired companies to mass-produce calcium-based products. Many of these, such as OSTEOSET(r)-T (resorbable alpha hemihydrate calcium sulfate + tobramycin) have received approval by the Food and Drug Administration (FDA) in the US. However, a recent systematic review of 484 patients has highlighted that many of these papers have a significant risk of bias [69]. The authors therefore warn that while these results may seem promising, they are currently inconclusive [69]. Of those listed in Table 1, only [PERSON] et al. (2010) conducted a prospective randomised trial and even then, no blinding was put in place [70]. There is therefore a need for more recent, larger-scale randomised-control trials in this area [69]. Care should also be taken when extrapolating the results of studies based on osteomyelitisitis, to other contexts. It has recently been shown that antibiotic-impregnated calcium sulfate beads do not improve outcomes in periprosthetic joint infections, for example [71].
## 5 Study A--Without Tetralegia
### Study A--Questionnaire Results  
At the end of study A, each participant had to answer the INTUI and the NASA-TLX questionnaires. These questionnaires serve to evaluate the intuitiveness of the control schemes and how demanding it was to complete the tasks when using the different control schemes. Applying the Friedman test showed a statistically significant difference in the scores depending on the used control scheme, for both the INTUI (\(X^{2}(2)\ =\ 14.824,p\ <\ 0.001\)) and NASA-TLX (\(X^{2}(2)=15.846,p<0.001\)).  
A post hoc analysis of the results was performed using Wilcoxon, with Bonferroni correction for multiple comparisons, to identify statistical significance between the three control schemes. The results for the INTUI questionnaire show a statistically significant difference when comparing the non-autonomous control with either the adaptive semi-autonomous control (\(Z=-2.67,p=0.024\)) or fixed semi-autonomous control (\(Z=-2.67,p=0.024\)). This statistical significance is also indicated in the box plot of the scores shown in Figure 9a. From the box plot it is also clear that the significant difference is an improvement, i.e., an increase in the score, in favor of both the adaptive and fixed semi-autonomous control. However, there is little to no difference when comparing the adaptive and the fixed semi-autonomous control, and no statistical significance was found (\(Z=-0.341,p=1.0\)).  
A similar trend is seen for the results of the NASA-TLX questionnaire in Figure 9b. There is a clear and significant improvement, i.e., decrease, in the task load when using either the adaptive semi-autonomous control (\(Z=-2.807,p=0.015\)) or the fixed semi-autonomous control (\(Z=-2.805,p=0.015\)) in comparison to the non-autonomous control. The results of the comparison between the adaptive and fixed semi-autonomous control are similar to what was observed for the INTUI questionnaire as there is no significant difference (\(Z=-1.423,p=0.465\)).  
The results for the two questionnaires would have suggested that both hypotheses, **H1**: _The adaptive semi-autonomous control is better than the non-autonomous control_, and **H2**: _The fixed semi-autonomous control is better than the non-autonomous control_, are true. The last hypothesis, **H3**: _The adaptive semi-autonomous control is better than the fixed semi-autonomous control_, cannot be confirmed based on the results from the questionnaires.
# Developmental History of Soil Concepts from a Scientific Perspective
## 3 Results
### Early Studies of Soil Concepts
\begin{table}
\begin{tabular}{c c c c c c c c} \hline
**Soil Concepts** & **Year** & **Author** & **Tiles** & **Name of Journal** & **Volume** & **Issue** & **Pages** \\ \hline Soil Fertility & 1917 & [PERSON] & The Significance of Nitrification as a Factor in & _Communications in Soil Science and_ & 3 & 5 & 399-416 \\  & & [PERSON]; [PERSON]; & Soil Fertility & _Plant Analysis_ & & & \\ Soil Conservation & 1947 & [PERSON]; [PERSON]; & Development of Our National Program of Soil & & & & \\  & & [PERSON]; [PERSON]; & United States & & & & \\ Soil Productivity & 1948 & [PERSON] and [PERSON] & Influence of Earthworms on Soil Productivity & _Sul Science_ & 66 & 6 & 421-428 \\ Soil Quality & 1971 & [PERSON] & A Method for Rating Soil Quality & _Sul Science-USSR_ & 3 & 1 & 40-+ \\ Soil Protection & 1974 & [PERSON]; [PERSON] & Soil Protection for Spot/Production & Soil Conservation & 39 & 11 & 14-16 \\ Soil Sustainability & 1992 & [PERSON] & Achieving Soil Sustainability & _Journal of Soil and Water Conservation_ & 47 & 2 & 156-157 \\ Soil Health & 1992 & [PERSON] & A Soil Health Index & _Journal of Soil and Water Conservation_ & 47 & 1 & 6–6 \\  & & & & & & \\ \multicolumn{6}{c}{Tililage Effects Soil Organization, Soil} & \multicolumn{1}{c}{} & \multicolumn{1}{c}{} & \\ Soil Resilience, Soil Quality, and & \multicolumn{1}{c}{} & \multicolumn{1}{c}{} & \multicolumn{1}{c}{} & \\  & & & & & & \\  & & & & & & \\  & & & & & & \\  & & & & & & \\ Soil Care & 1994 & [PERSON] & Soil Care and The USA National Debts & & & & \\  & & & & & & \\ Soil Security & 2013 & [PERSON] and [PERSON] & Framing Soils as an Actor When Dealing with & & & & \\  & & & & & & \\  & & & & & & \\  & & & & & & \\  & & & & & & \\  & & & & & & \\  & & & & & & \\  & & & & & & \\ \end{tabular} \({}^{1}\) Seven authors published article in a journal in the same volume volume and issue, which investigated the different regions of the United States. Each tile was listed in the order of authors in this table. Development of Our National Program of Soil Conservation; Soil Conservation and Good Land Use in the Northeastern Region; Soil Conservation and Good Land Use in the Northeastern Region; Soil Conservation and Good Land Use in the Northeastern Region; Soil Conservation and Good Land Use in the Northeastern Region; Soil Conservation and Good Land Use in the Northeastern Region; Soil Conservation and Good Land Use in the Pacific Region.  
\end{table} 
Table 5: Search results of soil concepts in soil science journal articles (1900 to 2017), Web of Science. Several soil science journals published pioneering work for different soil concepts (Table 5). For example, CSSPA recorded the earliest articles for soil fertility and soil care; SSJ produced the earliest articles on soil conservation and soil productivity concepts; and the _Journal of Soil and Water Conservation_ (SWC) produced the earliest work on soil sustainability and soil health. These journals appeared before 1974 and can be classified as relatively old journals for soil concepts.
## 1 Introduction
It is found that the recombination parameter \(J_{01}\) of the diffusion region and the recombination parameter \(J_{02}\) of the depletion region of PERC solar cells are smaller than those of Al-BSF solar cells under the same injection level. This result shows that a PERC silicon solar cell has high carrier collection efficiency under different injection levels compared with an Al-BSF solar cell. According to the obtained recombination parameters, the current-voltage equation of solar cells can be established under different injection levels, and the daily energy production can be calculated accurately. An interesting finding is that the \(J_{01}\) of an Al-BSF solar cell increases quickly with the decreasing injection level compared with a PERC silicon solar cell. This reveals that the output performance of an Al-BSF solar cell decreases rapidly when the injection level is getting low compared with a PERC silicon solar cell. In order to improve the performance of Al-BSF solar cells under low irradiance, the \(J_{01}\) must be reduced by decreasing process contamination and good passivation. Finally, the relationship between the \(J_{01}\)/\(J_{02}\) and injection level for Al-BSF and PERC solar cells is investigated under different injection levels, and the effects of \(J_{01}\)/\(J_{02}\) on open-circuit voltage, short-circuit current density, and fill factor are also analyzed under different injection levels. The results indicate that the recombination behavior of different cell regions will change with the injection level, and the ratio of \(J_{01}\)/\(J_{02}\) under different injection levels will affect the output performance of Al-BSF and PERC solar cells. The conclusions obtained in this article not only clarify the relationship between the recombination parameter and injection levels under non-standard test conditions, but also help to optimize solar cell processes and accurately model daily energy production for crystalline silicon solar module energy rating purposes.
## 2 Methodology
### Probability-Based Robustness Index  
The second part of the computation model is the probability-based robustness index. As the common evaluation index, \(BER\) indicates the watermarking algorithmic robustness in a single experiment, the calculation method refers to Equation (2). It cannot be used, however, to directly compare the \(NC\) of different watermarking algorithms, due to the different experimental parameters and conditions. To more conveniently and comprehensively measure robustness, a quantitative index \(R\) is proposed from the perspective of probability. Here \(R\) is defined as the probability of successfully and correctly extracting the watermark information after attack according to the given threshold value \(BER^{*}\). As \(BER^{*}\) is usually a constant value in the system of robustness evaluation, it is often omitted and index \(R\) is then expressed as:  
\[R(AT,S,L,N). \tag{3}\]  
In Equation (3), \(AT\) represents the attack type, and in this paper denotes image cropping. \(S\) is the attacking strength indicating that cropping \(S\) percentage of data. \(L\) is the watermark information length and \(N\) represents the repeat times of the embedded watermark.  
From the definition of index \(R\), the superiorities of the proposed index, compared to traditionally used ones are explained as follows. First, robustness is evaluated by probability, thus the more times experiments are repeated under the same parameters of attack, the greater the likelihood that the evaluated value \(R\) will approximate to the theoretical value. Then, \(R\) has no relationship to the sample data. Hence this index has universal usage and contributes to the comparison of the robustness of different algorithms conveniently. In addition, providing the attacking strength is well defined, the proposed index is not limited to the image cropping discussed in this paper. Hence, this quantitative index is applicable to all kinds of attack. Accordingly, the universal index R can be used to evaluate robustness more scientifically and comprehensively.  
Figure 6: An example demonstrating Principle 4.
# A Digital Bang-Bang Clock and Data Recovery Circuit Combined with ADC-Based Wireline Receiver
## 2 The Working Principles of the MMPD and DBBPD  
### The Working Principles of the MMPD  
The MMPD infers channel responses from baud-rate samples of the received data. The adaptation aligned the sampling clock such that the pre-cursor \(h_{-1}\) was equal to the post-cursor \(h_{1}\) in the pulse response, as shown in Figure 1.  
Figure 1: The convergence goal of the MMPD.  
The timing function \(f(\tau)\) defined in [6] is expressed as:  
\[f(\tau)=\frac{1}{2}(h_{1}-h_{-1}) \tag{1}\]  
where \(h_{1}\) and \(h_{-1}\) represent the amplitudes of the post-cursor and pre-cursor, respectively. Algorithms choose their steady-state timing in such a way as to yield equal values for \(h_{1}\) and \(h_{-1}\). If \(h_{1}\) is greater than \(h_{-1}\), the sampling time of the CDR circuit is early. Similarly, if \(h_{1}\) is less than \(h_{-1}\), the sampling time of the CDR circuit is late.  
The generation of the MMPD timing estimator \(z_{k}\) in binary signaling format defined in [6] is shown in Figure 2a and is expressed as:  
\[z_{k}=\frac{1}{2}(x_{k}d_{k-1}-x_{k-1}d_{k}) \tag{2}\]  
\[E\{z_{k}\}=\frac{1}{2}(h_{1}-h_{-1})=f(\tau) \tag{3}\]  
where \(x_{k}\) is the received sample and \(d_{k}\) is the signal decision value (\(d_{k}\) can only have a value of \(\pm 1\)).  
Thus, the results of the timing function \(f(\tau)\) are transformed into the expectation of the timing estimator \(z_{k}\). The analog samples \(x_{k}\) are converted into digital signals \(s_{k}\) after the ADC. The comparison between \(x_{k}\) and \(\pm V\!ref\) can generate error signal \(e_{k}\). The values of \(d_{k}\), \(e_{k}\) and \(s_{k}\) are shown in Figure 2b. According to the results of \(d_{k}\) and \(e_{k}\), the expression of \(s_{k}\) can be obtained as:  
\[s_{k}=d_{k}(e_{k}+1)/2 \tag{4}\]  
Thus, the MMPD timing estimator \(z_{k}\) can be converted into:  
\[\begin{array}{ll}z_{k}&=(x_{k}d_{k-1}-x_{k-1}d_{k})/2\\ &\sim(s_{k}d_{k-1}-s_{k-1}d_{k})/2\\ &z_{k}=d_{k}d_{k-1}(e_{k}-e_{k-1})/4\end{array} \tag{5}\]  
Equation (5) illustrates how a phase error is detected based on the signs of two consecutive samples and the signs of two consecutive errors. A waveform diagram of this phase error detection is shown in Figure 3 and the phase error values are listed in Table 1. It can be clearly seen from Figure 3 that if \(V\!ref\) is not set properly, it affects the value of \(e_{k}\), which, in turn, affects the up/down signal generated by the MMPD.
## 5 Our Approach
### Application of RDE to Detect Outliers' Calls  
In this section, instead of analysing the behaviour of the callers (as it was done in previous sections), all the calls are analysed to detect outliers' calls in real-time. In this sense, as it was previously explained, the initial dataset was represented by 9834 calls and the features that can be collected (without pre-processing) from the calls data set are the following:  
Figure 6: Plot of the density of the 4000 observations (10 days \(\times\) 400 users) from _CallsDay6h_. The information of one outlier caller is described.  
* duration of the call;
* time when the call has been made; and
* location of the call-originating mobile tower.  
Considering these three data, a data space in which are measured all the call data is created. Thus, for each new call, these three data are normalized and then its density is calculated recursively; if it is lower than a threshold, it means that the current call is significantly different (in terms of the three analysed features) than the previous calls. In this case, the normalization process is also very important since the three data are relevant to calculate the RDE.  
Figure 7 shows the density of the 9834 calls. Some of those calls are very different than the previous ones, as their density is much lower. In this case, a call is considered as outlier if its density is lower than 3\(\sigma\). In that case, the corresponding information about the call and the caller can be analysed in detail. Below, two of these outlier calls are described:  
* Outlier call #1346: This call was made by the user #370 and the id of the receiving user is #49. The date of the call is day 2 at a time from 12:00 to 13:00, and it lasted only seven seconds. The location of the call origination cell tower is 1.
* Outlier call #5841: The user #349 made this call to the user #23. The call started at a time from 11:00 to 12:00, and it was made in the day 6. Its duration was of 1738 seconds and the location of the call-originating cell tower is 2.  
In addition, it can be observed from Figure 7 that during the day 8, there are 30 outlier calls. In this sense, it is important to remark that the dataset used in this research is a synthetic dataset (CDRs), and the designers of these data possibly wanted to differentiate a day in which the calls were very different than usual. In real life, it can also happen since, for example, the calls on weekends or holidays are much more different than the calls during working days. However, these kinds of \"special days\" could be detected in advance and the RDE could be calculated considering only those days.  
Finally, it is very important to remark that all the previous calls are considered to detect outliers. However, since there is no need to store all those calls, the proposed method is computationally very efficient and the outliers can be detected in real-time. In addition, since the calls' data are not stored, it supports the privacy of customers.  
Figure 7: Plot of the density of the 9834 phone calls. The information of two outlier calls are described.
# Uncertainty Theory-Based Resilience Analysis for LEO Satellite Communication Systems
## 4 LEO-SCS and Its Uncertain Evolution Model
### Uncertain Satellite Network Evolution Model
#### 4.2.2 Uncertain Satellite Network Evolution Modeling Method  
Considering that only limited performance data (e.g., processing delays) can be obtained in an LEO-SCS, the system has the following three characteristics:  
* Its topology is dynamic and predictable [22];
* Satellite failure changes the network topology [27];
* Processing delays, which largely affect the end-to-end delay of an LEO-SCS [22], have epistemic uncertainty during system development.  
To the best of our knowledge, no researcher has simultaneously considered all three of these characteristics in LEO-SCS modeling. Therefore, we propose an uncertain satellite network evolution modeling method, using a dynamic, uncertain satellite network model to characterize the epistemic uncertainty of satellite performance (i.e., the processing delay) and topology dynamics and applying the evolution rule of the dynamic, uncertain satellite network model to describe the topology evolution process of an LEO-SCS with satellite failures and recoveries.
# An Integrated DQN and RF Packet Routing Framework for the V2X Network
## 3 Design of the IDRF System
### Offline Phase  
This study employed vehicle trajectory data from the Beijing city taxi dataset, sourced from the Microsoft platform [25; 26; 27]. The dataset encompasses GPS trajectories of 10,357 taxis within Beijing city on 2-8 February 2008. It comprises approximately 15 million recorded points, spanning a cumulative distance of 9 million kilometers. First, we defined a specific region within Beijing city and removed data points from outside the area. The map used in this study encompasses latitudes 39.89851 to 39.94923 and longitudes 116.36701 to 116.41253. The dimensions of this map are a length (\(L\)) of 3880 m and a width (\(W\)) of 5636 m. Since the original trajectory data do not include information about specific road segments and intersections traveled by vehicles, we annotated the coordination of 72 intersections within the region as {\(I_{i}\), \(I_{j_{r}}\),..., \(I_{x}\)}. Each road segment is formed by two adjacent intersections labeled {\(S_{i}\), \(S_{j}\),...,\(S_{x}\)}, making 110 road segments in total (Figure 7). Moreover, we incorporated the intersection and road segment serial numbers into the original trajectory data. The modified information is presented as follows (Figure 8):