esa-sceva/satcom-chunk-collection huggingface dataset:
# An Effective AUSM-Type Scheme for Both Cases of Low Mach Number and High Mach Number
## 2 Governing Equations  
Generally, the motion of the fluid can be described by NS equations, which can be written as follows [24; 25]:  
\[\mathbf{s}=\
abla\mathbf{q} \tag{1}\]  
\[\frac{\partial\mathbf{q}}{\partial t}+\
abla\cdot\mathbf{f}_{c}(\mathbf{q})-\
abla\cdot\bm {f}_{v}(\mathbf{q},\mathbf{s})=0 \tag{2}\]  
where \(\mathbf{q}\), \(\mathbf{s}\), \(\mathbf{f}_{c}(\mathbf{q})\) and \(\mathbf{f}_{v}(\mathbf{q}\),\(\mathbf{s})\) are the conservative variable vector, the auxiliary variable vector, the inviscid flux vector and the viscous flux vector, respectively.  
\[\mathbf{q}= (\rho,\rho u,\rho v,\rho e)^{T} \tag{3}\] \[\mathbf{f}_{c}(\mathbf{q})=\begin{pmatrix}\rho u\\ \rho u^{2}\\ \rho uv\\ (\rho e+p)u\end{pmatrix}\overset{\rightarrow}{i}+\begin{pmatrix}\rho v\\ \rho uv\\ \rho v^{2}\\ (\rho e+p)v\end{pmatrix}\overset{\rightarrow}{j}\] (4) \[\mathbf{f}_{v}(\mathbf{q},\mathbf{s})=\begin{pmatrix}0\\ \tau_{xx}\\ \tau_{xy}\\ u\tau_{xx}+v\tau_{xy}+b_{x}\end{pmatrix}\overset{\rightarrow}{i}+\begin{pmatrix} 0\\ \tau_{xy}\\ \tau_{yy}\\ u\tau_{xy}+v\tau_{yy}+b_{y}\end{pmatrix}\overset{\rightarrow}{j}\] (5) \[\tau_{xx}=2\mu\frac{\partial u}{\partial x}+\left(\beta-\frac{2}{ 3}\mu\right)\left(\frac{\partial u}{\partial x}+\frac{\partial v}{\partial y }\right)\] (6) \[\tau_{yy}=2\mu\frac{\partial v}{\partial y}+\left(\beta-\frac{2}{ 3}\mu\right)\left(\frac{\partial u}{\partial x}+\frac{\partial v}{\partial y }\right)\] (7) \[\tau_{xy}=\mu\left(\frac{\partial u}{\partial y}+\frac{\partial v }{\partial x}\right)\] (8) \[b_{x}=\kappa\frac{\partial T}{\partial x}\] (9) \[b_{y}=\kappa\frac{\partial T}{\partial y} \tag{10}\]  
where \(\rho\) is density, \(u\) and \(v\) are the components of the velocity vector. \(p\), \(e\), \(T\), \(\mu\), \(\beta\) and \(\kappa\) are the static pressure, the internal energy, the temperature, the dynamic viscosity, the bulk viscosity and the thermal conductivity coefficient, respectively. More information about the governing equations is available in Ref. [26].
## 3 Results
### Extent of Irrigated Area
#### 3.1.1 Sudan  
The identified irrigated area in Sudan clearly decreases with coarser spatial resolution. At a resolution of 100 m, the irrigated area decreases by 7% and continues to decrease to 29% at a resolution of 1000 m (Figure 3 and Table 1). At a coarser resolution of 300 m, single small-scale fields are no longer classified as irrigated, especially when they are surrounded by non-cultivated or abandoned fields or non-vegetated areas. This effect decreases the extent of irrigated areas. Figure 5 shows that contiguous clusters of fields are less affected by resolution decrease. At the finer resolutions (below 300 m), the fields are well defined and differentiation between fallow fields, possible artificial area and other irrigated fields is possible. At the coarser resolutions (from 300 m upwards), the areal extent decreases and the original patterns are hardly visible.  
Figure 4: Mapped irrigated area as a function of spatial resolution in the three different study sites: **A** = China, **B** = Sudan, **C** = USA. **1** = 10 m, **2** = 300 m, **3** = 1000 m.  
Figure 5 shows the center pivot fields in the northwestern part of the Sudan tile. This detail serves as a good example of the decrease in the irrigated area. At the finer resolutions, the center pivot fields can clearly be identified. At a resolution of 300 m, the center pivot fields dissolve and almost completely disappear at the resolution of 1000 m.
# Application of Collision Warning Algorithm Alarm in Fishing Vessel's Waterway
## 4 Application in Fishing Vessel's Waterway Based on Vpass Data
### Case Study of the Collision Warning Algorithm Application Based on Vpass Data
#### 4.2.2 Comparison between Waters with Alarms and Risky Waters
In particular, the areas with legs 78 and 80 that had many alarms and were risky according to the PARK model are heavy traffic waters, because the waterways approaching the pilot station and Daesan Harbor as well as the silica mine extraction zones are collocated [36]. In Figure 12a,d, the high-risk water assessed by IWRAP and the alarm-prone zone did not match compared with other risk-assessment tools. This is because IWRAP evaluates risk based on traffic flow, whereas fishing boats do not have a particular route pattern, owing to their characteristics. Thus, there seems to be a low rate of coincidence.
# Remote and Proximal Sensing Techniques for Site-Specific Irrigation Management in the Olive Orchard
## 2 Materials and Methods
### Statistical Analysis  
The SWP was measured in six trees per irrigation regime (three trees per cluster-irrigation combination) and the means were separated by the least significant differences (LSD \(p>0.05\)) after analysis of variance (ANOVA). An exploratory correlation analysis was performed between NDVI, soil proximal sensing (ECa\({}_{1}\), ECa\({}_{2}\), TC\({}_{\text{gamma}}\)), fruit yield, and TCSA increment, to highlight the statistical relationships between the main parameters used for this study. Since most of them showed non-parametric distribution, the Spearman's ranks correlation test was used. In particular, correlation models within the different irrigation regimes (FI, DI and RF) have been tested by linear regressions. Full factorial ANOVA was carried out to test the effects of the irrigation regimes categorial factors (FI, DI, RF) and homogeneous zones (C1 and C2), as well as the combinations of these factors. Post-hoc LSD Fisher test was used to determine the significant differences between the means of the analysis of variance. To determine the influence of PSS data and NDVI on fruit yield and annual TCSA increment predictions, forward-stepwise multiple  
Figure 1: False colour orthophoto of the olive orchard located at the experimental farm of the Department of Agriculture Food and Environment of the University of Pisa (43\({}^{\circ}\)10\({}^{\prime}\) N; 10\({}^{\circ}\)36\({}^{\prime}\) E). The canopies of the olive trees cv. Frantoio are in green (Cluster 1) or light blue (Cluster 2). The trees of other cultivars were not used in the experiment.  
regressions were calculated for each irrigation treatment (FI, DI, RF). The independent variables used for the regressions were \(\text{ECa}_{1}\), \(\text{ECa}_{2}\), \(\text{TC}_{\text{gamma}}\), and NDVI. The selection of variables by the forward-stepwise regression was carried out on the basis of F-to enter of 3, to avoid a nonsignificant contribution of some variables in the regression. Statistical analyses were performed with STATISTICA 7.0 (StatSoft Inc., Tulsa, OK, USA).
## 4 Experiment and Discussion
### Worldwide Availability Coverage Test  
The ARAIM TSG focuses on the ARAIM algorithm based on GPS and Galileo. The baseline configurations used in the milestone report have 24 GPS satellites and 24 Galileo satellites, where GPS is the 24-slot nominal constellation and Galileo is a Walker 24/3/1. It is also the nominal constellation of the above two systems. BDS MEO and GLONASS system have a similar constellation configuration to Galileo, and the nominal number of BDS MEO satellites is reduced to 24 in BDS-3 generation. The GEO satellites and IGSO satellites are not considered in this subsection as they cannot cover the whole earth. Therefore, the baseline configurations of four constellations are: 24 GPS satellites, 24 GLONASS satellites, 24 Galileo satellites, and 24 BDS MEO satellites. The above configurations are accepted in this paper to analyze the worldwide performance of ARAIM in different modes. All GNSS observations are generated using the adjusted real almanacs.
## 5 Experimental Results and Analyses  
### Bridge Node Prediction Experiment  
First, we conducted bridge node detection experiments on five real networks. In this part of the experiment, we used selected features to generate the feature vector of the node, and trained and tested the models on this basis. The experiments included our three proposed models--BND-GCN, BND-GraphSAGE, BND-GAT--and four baselines. Table 3 shows the test results of these models on various networks.  
For each metric, we bolded the highest score obtained in each network. Experimental results on five networks of different sizes show that our proposed BND-GCN model exhibits outstanding advantages compared with baseline models on the task of identifying bridge nodes between communities with known communities. In addition, the two variants of BND-GCN, BND-GraphSAGE and BND-GAT, also perform well. Compared to traditional methods, GNN-based methods show that the attribute graph constructed by selecting node features can describe the network structure well, so as to achieve a good embedding effect. On the other hand, the BND-GCN model is more robust compared to the baseline method Inf-GCN according to the results. This may be due to improvements we made to the model.
## 4 The Considered Nodes' Synchronization and Data Transmission Protocol  
The proposed network architecture is composed of a set of \(S\) sensor nodes arranged as a chain, with sensor node 1 transmitting to the adjacent node 2 which will then forward the packet to node 3 an then on and on in a similar fashion down to node \(S+1\) which acts as a gateway forwarding the received packets to a data management centre. While the topology is fixed, the position of each node in the network is known a priori: this means that also the role of each node is known in advance.
## 4 Performance Evaluations
### Lake Experiment
Since the experimental data were collected at a high SNR, the performance of the DAM-TEQ was also verified by adding additional Dongjiang Lake environmental noise to the original data during processing, as shown in groups 2, 4, and 6 in Table 3. After the SNR is reduced by about 5 dB, the BER performance trend is basically unchanged, and only group 4 cannot eliminate the interference effect of noise by the equalizer due to the low SNR. The results show that the DAM-TEQ maintains a great advantage and that some experimental groups can maintain the information transmission without error by increasing the number of iterations. In addition, a set of communication signals that were  
Figure 7:0 The constellation diagrams processed by the two equalizers. heavily disturbed was also processed, and the associated peaks could not be accurately estimated, as shown in group 7 in Figure 7:1 Although the final BER is still relatively high, the performance of the proposed equalizer is greatly improved compared with the conventional method, which further illustrates the advantages of the DAM-TEQ.
## 5 Case Studies: Validating the CILS Framework
### Case Study Two: HelloTalk
#### 5.2.2 Application of the CILS Framework in HelloTalk  
Integrating the CILS within HelloTalk has revolutionized how the app supports language learning through real-time interactions. By applying the CILS, HelloTalk can enhance its capabilities to offer personalized learning experiences sensitive to each interaction's cultural nuances. This integration brings AI-driven analytics and adaptive learning technologies into the platform, providing a richer, more context-aware learning environment.  
With the CILS, HelloTalk can analyze communication patterns and adapt conversations to suit the user's learning needs. For instance, if a learner struggles with certain cultural concepts or linguistic structures, the CILS can dynamically adjust the content or suggest resources within the chat. This might include culturally informative snippets, idiomatic expressions relevant to recent topics, or corrective feedback on language mistakes, all provided in real time.  
The CILS framework enables HelloTalk to implement scenario-based learning, where learners can engage in tailored dialogues designed to simulate specific cultural interactions. These scenarios help learners practice appropriate language use in varied social contexts, enhancing their linguistic and cultural competence. AI-driven modifications ensure these scenarios align with the learner's progress and personal learning goals.  
The application of the CILS in HelloTalk improves linguistic accuracy and deepens cultural understanding, which is often missing in traditional language learning apps. By fostering an environment where language learning is continuously informed by cultural insights, HelloTalk with CILS becomes a more powerful tool for preparing learners to communicate effectively across cultural boundaries. This holistic approach to language education is particularly beneficial in our globally connected world, where understanding and navigating cultural diversity are as important as linguistic proficiency.
## 1 Introduction
### QRA in Tunnels  
Quantitative Risk Assessment (QRA) was applied long ago, firstly in the nuclear and then in the process and chemical industry. Nowadays, it applies to many everyday activities such as air, land, and sea transport, all types of industrial sectors, and occupational safety. The main questions (in simple words) that have to be answered during a QRA process are:  
1. What might go wrong;
2. How often this might happen;
3. What are the consequences;
4. How harmful (i.e., life-threatening, environment and assets) these consequences might be.  
Different organizations prepare QRA guidelines in various sectors, mainly referring to dangerous-to-life situations. That is one of the main reasons that different scenarios of fire accidents have to be included in the QRA of tunnels according to the guidelines of the Organisation for Economic Co-operation and Development (OECD), the European Union (EU), and the World Road Association (PIARC). In the OECD/PIARC/EU Dangerous Goods QRA model [17; 18; 19], 13 scenarios are included covering the major dangers that may result in numerous victims and injuries, along with serious damage to the tunnels' structural integrity, namely fire, explosion, and toxic release. Scenarios include the following: HGV fire 20 MW, HGV fire 100 MW, BLEVE of LPG (cylinder), Motor spirit pool fire, VCE of motor spirit, BLEVE of LPG (bulk), VCE of LPG (bulk), Torch fire of LPG (bulk), BLEVE of carbon dioxide (bulk), Chlorine release, Ammonia release, Acrolein release (bulk and cylinder) [20]. Furthermore, a quantitative risk assessment process has been proposed by [21] for trucks carrying hydrogen, and an overview of fire characteristics and smoke control methods have been outlined by [6]. The above shows the importance of knowing precisely the substance entering a tunnel at any time.
# A Comparative Study of Indoor Accuracies Between SLAM and Static Scanners
## 2 Materials and Methods
### Processing and Evaluation of the Acquired Data  
#### 2.6.1 Initial Processing  
This experiment was devised to mimic the everyday practical use of the scanners. Before the evaluation, the point clouds were cleaned of undesirable points (scanned moving persons, obvious noise, etc.).  
As any point cloud represents a complex representation of the scanned space, multiple characteristics were used for the evaluation of the results. Regardless of the type of scanner, further processing of the primary clouds acquired from the proprietary software was performed in CloudCompare v. 2.12.  
First, the clouds acquired using the static scanners were diluted. The reference cloud was diluted to a density of 4 mm to maintain high surface detail. Clouds from the tested static scanners were diluted to 1 cm to even out the density (there were places with excessive density, especially in the vicinity of the scanning stations). No point cloud reduction was performed in the SLAM scanners due to the character of the distribution of the points--in view of the high noise, such dilution would predominantly remove points from the most dense (most accurate) part of the distribution.  
Figure 6: Illustration of the two types of error in the shape of the point cloud (the size of error is characterized by the vertical deviation from the reference cloud–black line). Random error (blue line) remains similar along the entire cloud (i.e., along the scanned path), while the systematic error is lowest at the terminal points (where it is “pinned” to GCPs) and highest in the middle of the path. ICP transformation aims to minimize the overall error, which leads to approx. halving both the maximum and overall errors.  
Further evaluation utilized root mean square error (RMSE) as a metric and served to compare (i) the whole clouds and (ii) specific sections of the cloud to obtain further information.
# A LoRaWAN Architecture for Communications in Areas without Coverage: Design and Pilot Trials
## 5 Results
### Experimental Set-Up
* The natural environment was located in \"Sierra Morena\" of Andujar in the province of Jaen. In each of these areas, the data capture experiment was performed three times. In each data capture, the data were obtained at distances of 0, 25, 50, 75, 100, 200, 300, 400, 500, 750 and 1000 m. Each trial consisted of 10 measurements for each of the mentioned distances. In this way, randomness of the measurements was avoided, and the measurements were thus reliable. For the measurements, design B in Figure 5 was used due to the areas where the experiments were performed being well known. The end nodes were implemented on PyCom Fipy devices. These devices are suitable for bidirectional communications due to their support for class C in MAC. In addition, they are small devices that emergency team members could comfortably carry with them. The central node was deployed on top of IMST Gateway Lite because of its higher accuracy in RSSI measurements and lower probability of error in signal capture [44]. On the other hand, LoRa modulation with a spreading factor (\(SF\) = 7), bandwidth (\(BW\) = 125 KHz) and coding rate (\(CR\) = 4/5) was used because it offered a data rate suitable for sending text messages (\(R_{b}\) = 5.47 Kbps). The results of this experiment are shown in Section 5.3.
# Investigation of a Solar-Driven Organic Rankine Cycle with Reheating
###### Abstract  
The purpose of this simulation study is the examination of a solar-driven power cycle that is driven by collectors with evacuated tubes. The power cycle is an organic Rankine cycle (ORC) that works with cyclopentane. The novelty of the cycle is the use of reheating in order to enhance its thermodynamic efficiency, while the cycle also has a recuperator. Moreover, the cycle is compared with the conventional ORC in order to determine the performance enhancement with the examined idea. The analysis is done with a developed program in Engineering Equation Solver and both in steady-state and transient conditions for a typical year. The analysis was conducted in terms of energy and economic performance. According to an optimization procedure for maximizing the net present values of the investment, it is found that the novel design leads to a net present value of 68 k\(\epsilon\), a simple payback of 10 years, and a yearly energy efficiency of 7.0%, while the respective values for the conventional ORC are 44 k\(\epsilon\), 10.8 years, and 5.1% for its optimal design according to the net present values maximization. Thus, it is obvious that the suggested design increases both energy and financial performance, compared to the usual design.  
solar energy; ORC; reheating; dynamic analysis; evacuated tube collector Article
## 4 Numerical Results and Discussions
### Bit-Error-Rate
#### 4.1.2 Bit-Error-Rate in S\({}_{2}\)  
Figure 8 demonstrates BER performance of NU in S\({}_{2}\) as a function of SNR for different order of PSK and QAM modulation, considering the BS and NU are equipped with the same number of of antennas. Here, SNR ranges between 0 to 30 dB. In each instance, BER gradually declines with increasing SNR which is expected. We observed that for both PSK and QAM higher order of modulation corresponds to higher BER. As we mentioned before, this is because of the fact that when the number of modulation order increases, the likelihood of erroneous detection of constellation points increases. We also noticed that for higher order of modulation BER performance with QAM is better compared to the ones with PSK.  
Figure 5: BER of FU in S\({}_{1}\) for \(M\)-PSK.  
In Figure 9, we portrait e2e BER performance of FU in S\({}_{2}\) with respect to SNR, where SNR holds values from 0 to 30 dB. The term in inset represents the following parameters: (i) \(A_{\text{BS}}\), \(A_{\text{D}_{1}}\), and \(A_{\text{FU}}\) denote the number of antennas at BS, D\({}_{1}\) and FU, respectively, and (ii) D\({}_{1}\) exploits SM to forward de-mapped FU information with \(2^{N_{1}}\)-PSK/QAM modulation. It is noted that an increase in the number of antennas at FU improves the BER performance, considering the same number of antennas at BS and D\({}_{1}\). When the number of antennas at a receiver increases, the diversity order increases, which in turn improves the BER of FU with an increase in the number of receiving antennas. It is also observed that the improvement in BER is dramatic when the BS and D\({}_{1}\) are equipped with higher number of antennas.  
Figure 6: BER of FU in S\({}_{1}\) for \(M\)-QAM.  
Figure 7: BER comparison among the users in S\({}_{1}\).  
In Figure 10, we show BER of the different users in S\({}_{2}\) against SNR for a comparative analysis. The legend terms denote the corresponding information as we mentioned for the previous two figures and additionally includes the transmitted number of data bits. Considering similar antenna configurations at the nodes involved in transmission, it is noticed that BER of NU is lower than other two users (D\({}_{2}\) and FU) while BER of FU is higher than others for the transmission of same number of data bits.  
Figure 8: BER of NU in S\({}_{2}\).  
Figure 9: BER of FU in S\({}_{2}\).
###### Abstract  
With the rapid increase in the number of various terminal devices in distribution systems, the important impact of communication networks on power supply reliability in cyber-physical distribution systems (CPDSs) is becoming increasingly prominent. The traditional wired communication method makes it difficult to meet the demand in some scenarios due to high cost and construction difficulty. For this reason, this study evaluated the reliability of power distribution cyber-physical systems, considering fifth-generation (5G) mobile communication technology wireless access conditions. First, a reliability model of a communication channel in a 5G communication network was established, and the indirect impact of information system failure on the power distribution system was analyzed. Secondly, a reliability assessment method based on the improved least path method was devised by combining switch action failure, self-healing processing, and load transfer. The simulation results show that 5G communication technology has significant advantages in improving system reliability, and the proposed method is closer to the development direction of future power distribution systems, which provides an effective reference basis for the optimized operation of power distribution cyber-physical systems.  
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