esa-sceva/satcom-chunk-collection huggingface dataset:
# Methodology for Conceptual Navigational 3D Chart Assessment Based on Eye Tracking Measures
## 1 Introduction
### Technological Challenges  
Given technological developments, the visualisation of cartographic information is also changing. Nowadays, this information can take different forms, going beyond the predefined IHO standards, as can be observed in various Marine GIS systems [6; 7; 8; 9; 10; 11]. Other forms and techniques for presenting nautical and maritime information may include the marine environment [12], conception of spatial presentation of ENC [13], web ENC [14], GIS systems with their own cartographic signs representing features in the area [15; 16], 3D visualisation [17], marine cadastre [18], underwater topography [19], dynamic ENC map presentation [20], 3D data fusion [21], use of 3D data in simulators [22], land-based piloting [23], and real-time navigation monitoring [24].  
It should also be borne in mind that new forms of visualisation are often created by the type of device. In the case of navigation maps, one can mention the increasingly widespread use of mobile phones or smartwatches. Reducing the visualisation area of quite complex navigation information can be a considerable challenge in optimising map effectiveness, especially when considering the small display sizes of smartwatches in the order of 30-35 mm and a resolution of 240-280 pixels [25].  
New trends go even further towards augmented reality [26]. An example of this technology in application to inland navigation can be found in [27] and for increased efficiency of ship manoeuvring in [28]. Ready-made systems using AR are offered by Raymarine [29] and Furuno [30]. At present, however, these are not standardised on ships, but nevertheless, due to their usefulness, they should soon become one of the navigational aids, enabling the necessary navigational information to be analysed quickly and efficiently. Given the changing possibilities of visualising nautical information, the development of effective forms of visualisation is a significant challenge, especially considering the navigational safety factor.
## 5 Simulation Analysis
### Simulation Results  
#### 5.2.1 Performance of Different Types of Packets  
The packet loss rates for the three types of services are shown in Figure 6a. It can be observed that the packet loss rate of the Dijkstra algorithm is significantly higher than the other two algorithms. For different services, the algorithm proposed in this paper performs better than the traditional GPSR in terms of packet loss rate. Specifically, the average loss rate of SQL-CBRP is about 21.5% lower than GPSR relatively. This is because the SQL-CBRP algorithm selects the neighbor node with the shortest queue as the next hop, which can effectively prevent packets from being forwarded to a node whose queue is already full, thereby reducing the probability of packet loss.  
The average delay results for the three types of services are shown in Figure 6b. It can be seen from the figure that for the three different service scenarios, the routing algorithm proposed in this study has shown some optimization in terms of delay compared to the GPSR algorithm. Specifically, the reduction in average delay is about 90 ms, which is about 11.0% lower than GPSR relatively. The emergence of this result is because SQL-CBRP takes into account both the queue length and the geographical location, which can reduce the queuing delay and propagation delay simultaneously.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter Name** & **Parameter Value** \\ \hline Number of satellite nodes & 80 \\ Distance between leaders & 600–700 km \\ Distance between leader and follower & 100 km \\ Nodes’ speed & 7.6 km/s \\ Nodes’ longest queue length & \(\mathfrak{g}\) \\ Rate of packet generation & 1 packet/s \\ Bandwidth of cluster head & 30 Mbps [20] \\ Simulation duration & 1500 s \\ Message service’s data rate & 15 Mbps [21] \\ Voice service’s data rate & 64 kbps [22] \\ Video service’s data rate & 8 Mbps \\ \hline \hline \end{tabular}
\end{table}
Table 2: Simulation parameters.
## 2 System Model
### Communication Model
#### 2.3.2 Data Rate Characterization of the D2D Link  
We also perform data caching at the UE level to increase data traffic offloading through the cache resources. This enables UE to obtain the desired content from proximal UE through D2D communications, given the availability of the requested content at the proximal UE and the availability of LoS link. Moreover, for D2D connectivity, both sets of UE should have LoS for mmWave data transmission. During D2D communications, the data-receiving UE experience interference from other D2D transmitters and cellular uplink UE that are operating at the same frequency. Thus, the transmission rate is evaluated as  
\[R_{v,n}=W\text{log}_{2}\left(1+\frac{P_{v}G_{t}(v,n)G_{r}(v,n)d_{v,n}^{-\delta }}{\sigma^{2}+\sum\limits_{k\in I\cap\{v\}}P_{k}G_{t}(k,n)G_{r}(k,n)d_{k,n}^{- \delta}}\right), \tag{7}\]  
where \(P_{v}\) is the transmission power of data-sending UE \(v\). \(G_{t}(v,n)\) and \(G_{r}(v,n)\) denote the directive antenna gains of the transmitter and receiver, respectively. \(d_{v,n}\) represents the distance between data-sending UE \(v\) and data-receiving UE \(n\), \(\delta\) represents the path loss exponent, and \(\sigma^{2}\) denotes the white Gaussian noise. \(G_{t}(k,n)\) and \(G_{r}(k,n)\) designate the directional antenna gains of interfering UE \(k\) and data-receiving UE \(n\), respectively. \(d_{k,n}\) represents the distance between interfering UE \(k\) and data-receiving UE \(n\), respectively.
## 5 Applications of Wireless EM Energy Transfer and Propagation in SCs
### IPT Batteries Charging in EVs in SCs
#### 5.2.6 Case of Exposure BEs in Human Body Nearby an EV  
A demonstrative example of ICT EMF exposure concerning the case of a human body placed on the ground horizontally adjacent to an EV while in static charging mode is given in this section [45]. Figure 8 displays the induced field distributions (of B and E fields) in the body due to ICT EMF exposure. The utilized human body model for computations relates to the high-resolution human structural model, is well-matched with the numerical 3D FEM approach used, and is presented in Figure 7. The induced B and E fields in the body tissues have been computed from the solution of (6)-(9), with a source field corresponding to the  
Figure 7: High-resolution human body model with its different organs and tissues, [45].  
stay fields of the ICT (3 kW at 30 kHz). The results were matched to the thresholds fixed by the safety standards [95,96] (27 \(\mu\)T for magnetic induction B and 4.05 V/m for the electric field E). In the present case, the results were in agreement with these safety guidelines.  
Figures 7 and 8 illustrate the use of a high-resolution human structural model, which is well-suited to the 3D FEM numerical approach used for matching an EMF-exposed body to thresholds set by safety standards for safety monitoring.
## Dynamic Key Sharing and Fuzzy Adaptive Route Selection
### Goals
#### 3.2.2 Fuzzy-Based Selection of Data Forwarding Path  
Our proposed method chooses the suitable path among the several available paths in response to input factors such as the number of verification nodes within \(h\) hops on every path, the residual energy status of the routing paths, and the distance between the e-CH and the BS via each path.  
Our proposed scheme uses FASIN as a submodule only for the adaptive selection of the intermediate verification nodes on the selected path.
## 5 Heuristic Algorithm Design  
Based on the topology abstraction-based routing scheme, in this section, we design three heuristic algorithms, i.e., GF-TAR, LF-TAR, and MS-TAR algorithms, to efficiently allocate the time and secret key resources in hybrid GEO/LEO quantum satellite networks. The notations and their definitions used in this paper are listed in Table 1.  
Figure 2: Illustration of topology abstraction-based (**a**) routing scheme and (**b**) key relaying strategy. The success probability (\(SPT(t_{i})\)) of the key service requests in the time slot \(t_{i}\) can be defined as follows. \[SPT(t_{i})=\frac{N_{\mathrm{r}}(t_{i})}{|R(t_{i})|} \tag{1}\]  
The success probability (\(SP\)) of the key service requests within the simulation time can be determined as follows (\(T\) is defined as the total simulation time). \[SP=\frac{\sum\limits_{i=1}^{T/\Delta}SPT(t_{i})}{T/\Delta} \tag{2}\]  
The average number of relaying hops (\(AHT(t_{i})\)) for the successful key service requests in the time slot \(t_{i}\) can be expressed as follows. \[AHT(t_{i})=\frac{N_{\mathrm{n}}(t_{i})}{N_{\mathrm{r}}(t_{i})} \tag{3}\]
# Hyperbolic Asynchronous Method of a Radio Navigation Technique
## 3 An Idea of the Asynchronous Radio Localization
### Logical Layer Description  
The following is a logical description of the transmission and reception paths used in reference stations, from the point of view of creating a signal with a navigation message as a data stream. It results from the proposed concept of the operation of a hyperbolic asynchronous system, based on access technology with direct DS-CDMA (Direct Sequence Code Division Multiple Access) [22].  
From this point of view, the most important functionalities of the transmission track are:  
* encryption, due to the purpose of this system,
* authentication,
* weave coding,
* packing, and
* a generation of distraction strings.  
The resulting logical scheme of the transmission path is shown in Figure 6.  
The operation of the transmitting part starts with entering basic and additional data into independent encryption blocks working with the AES (Advanced Encryption Standard) algorithm in CBC (Cipher Block Chaining) mode with a key length of 256 bits. Then, after encryption, the data is fed to the MAC AES CBS (Message Authentication Code AES CBS) block, which is a shortcut function for further authentication and for checking during transmission that the data has not been disturbed (changed) during transmission or due to intentional external interference. Further, in order to correct errors that may also occur during transmission in the radio channel, convolutional coding (2,1,9) with an efficiency of half has been used. In the next block of the broadcasting part, the packaging process is carried out, which consists of separating the encrypted navigation data, using pilot strings, and adding the beginning and end of the created frame at the beginning and end sequence as start and end markers of the transmission. In the next step, data are spread with a spreading sequence and, after passing through a pre-modulation filter, are fed on a QPSK modulator.  
The most important functionalities of the receiver are:  
* decoded weave codes
* depacking
* decryption  
In turn, the resulting logical scheme of the receiving track is shown in Figure 7.  
The receiver part is the opposite to a transmitter part. First, a modulated signal is divided into two branches. They are both put in a detecting unit (using [PERSON]'s algorithm). Next, depacking takes place. The last step is the decryption of data (using AES).
# A Comparison of an Adaptive Self-Guarded Honeypot with Conventional Honeypots
## 6 Experimental Results
### Collected Attack Data  
Table 1 shows the general statistics of the attack data that our honeypots received. Cowrie received the most attack episodes, while Aster received the least. Among those attack episodes, for Asgard, Midgard and Aster, only around 8% are really used for command execution, while the proportion reaches almost 17% for Cowrie; the rest are TCP/IP port forwarding requests. Even though Cowrie attracted the most attacks and also had the highest total number of commands, by closely looking at the average number of commands that each honeypot received per episode, Cowrie performed poorly, as it received only 5.51 commands on average compared to 18.48 commands for Aster, 9.68 for Asgard and 8.2 for Midgard. By examining the attack data, Cowrie received a large amount of the same single command echo -e \"\(\chi\)x6F\(\chi\)x6B\", which accounted for almost 51% of the total of attacks, which can explain its low average number of commands. These results confirm that the usage of a real system still performs best in terms of the average number of commands run per episode, although the adaptive honeypots were not far behind.  
Since most of the attacks were from automated programs and were very targeted, they mostly shared the same attack sequence. Let us be reminded that an attack sequence refers to a sequence of commands that are executed in an attack (cf. Section 4.1). For example, the three attack episodes below were captured in our honeypot and targeted Hive OS ([[https://hiveon.com/](https://hiveon.com/)]([https://hiveon.com/](https://hiveon.com/)), accessed on 15 April 2022), which is software to manage a mining farm. In attacks 1 and 2, the attackers first wanted to change the password of the user managing this farm by using the command hive-passwd followed by the new password. Next, they wanted to terminate any active user sessions by killing the processes Xorg and x11 vnc. These two attack sequences can be considered different or same. There are two methods that we can take into account: first, if we consider the commands with their arguments, then they are different, and, second, if we only consider the commands without their arguments, then they are the same because the two sequences of commands are the three commands sudo. However, attack 3 is different because of the command uname at the end.
# Geotechnical Evaluation of Diesel Contaminated Clayey Soil
## 3 Results and Discussion
### Influence of Diesel Contamination on the Soil's pH  
Soil contamination with diesel had a significant impact on its pH. After soil contamination, the pH of the soil changed from moderately alkaline (pH\({}_{\text{natural}}\) = 7.95 \(\pm\) 0.14) to neutral (pH\({}_{\text{contaminated}}\) = 6.98 \(\pm\) 0.03). Nevertheless, this pH drop does not represent a limitation for biodegradation processes, since the pH for the biotransformation of the contaminant has been found to be in the range of 6 to 8 [34]. This tendency to decrease the pH as the soil gets contaminated agrees with the results obtained by [PERSON] et al. [9].  
The pH reduction of soil after its contamination was due to the acidifying effect of the sulfur contained in diesel. It is known that the addition of elemental sulfur (\(S\)) to soil affects the oxidation rate and produces two hydrogen ions due to the microbial activity of soil (Equation (3)). Since pH is a measure of the hydrogen ion concentration (\(pH=-\log_{10}[H^{+}]\)) in soil solution, the increase in concentration resulted in a lower pH.  
\[S+CO_{2}+\frac{1}{2}O_{2}+2H_{2}O\ \to CH_{2}O+SO_{4}^{2-}+2H^{+} \tag{3}\]  
[PERSON] et al. [35] studied the effect of acid and alkaline waters on the geotechnical properties of clay soil and found that the decrease of the pH value of the soil increased the liquid limit and the plastic index of the soil. Moreover, they indicated that the coefficient of permeability of the soil increased as the pH values of the soil shifted from the neutral condition to the acidic or alkaline conditions [35].
## Materials and Methods
### Datasets  
This study was based on the PROBA-V Collection 1 (C1) top of canopy daily synthesis product obtained in the entire year of 2015. PROBA-V C1 images are produced every five days with a spatial resolution of 100 m at nadir and with radiometric and geometric corrections [39]. PROBA-V is the payload of a satellite mission to map land cover and vegetation and was designed to ensure continuity of the Satellite Pour l'Observation de la Terre Vegetation (SPOT-VEGFATION) mission [22; 40]. The sensor operates with four bands in the visible and infrared spectra (blue, 0.435-0.490 \(\upmu\)m; red, 0.610-0.700 \(\upmu\)m; near infrared (NIR), 0.760-0.930 \(\upmu\)m; and shortwave infrared (SWIR), 1.520-1.670 \(\upmu\)m). The PROBA-V mission also provides the status map (SM) information (pixel radiometric quality data) and the normalized difference data between the NIR and red bands, called the normalized difference vegetation index (NDVI) (not used in this study).  
As ancillary data, we selected two sets of Landsat-8 Operational Land Imager (OLI) satellite data obtained in 2015 (bands 4, 5, and 6 in the green, red, and NIR spectral regions, respectively; spatial resolution of 30 m; repeat pass of 16 days). One set was from the crop-growing season (July-December), and the other set was from the harvesting season (January-July). The MODIS-based time series of NDVI signatures available in the Satellite Vegetation (SATVeg) web tool, developed by the Brazilian Agricultural Research Corporation (Embrapa)1, were also used in this study. The LULC map of 2015, produced by the MapBiomas project, was the main vector-based data considered in this study.  
Footnote 1: Available in www.satveg.cnptia.embrapa.br. Accessed on 30 June 2019.
# Empowering WBANs: Enhanced Energy Efficiency Through Cluster-Based Routing and Swarm Optimization
## 4 Results and Discussion
### Packet Loss Ratio  
Figure 11 shows that ABBSOA and MSSOA show less losses and more consistent performance, gradually increasing MT-MAC, DHCO, ALOC, and M-GWO with maximum packet loss from 1000 to 5000 rounds. This emphasizes that ABBSOA and MSSOA maintain data reliability and security in communication networks.
## 4 Discussion
### Integrated Water Resource Management (IWRM) Recommendations
Our conceptual model concludes that properly installed and managed gravity-fed, mid- to upland-stream-source schemes offer the best prospect of high-volume supplies serving large population numbers. The potential for large-capacity borehole supplies appears fairly limited, with the possible exception of tapping permeable, fluvial gravels in the paleo-river channel subject to their water quality. Key considerations for stream/river-sourced gravity-fed schemes include:* Identification of locations for offtakes able to draw protected low-TDS water year round that use conjunctive groundwater supplies as buffer storage, and are hence situated at or below reaches receiving some dry-season perennial groundwater baseflow (or, less ideally some buffer storage is created via upland dams, or even perhaps aquifer storage and recovery (ASR)). It will be important to cross reference with the Malawi National Irrigation Plan so IWRM takes account of water supply and agricultural irrigation needs conjunctively. * Whilst borehole abstraction is recommended from elevations above the high-level deposit line, surface water offtakes could be similarly located, but could be viable somewhat further downstream if flows and low TDS remain reasonable and may help reduce pipeline lengths serving populations. * Offtake locations suitably located to: efficiently serve large populations numbers at lower elevations minimising pipeline lengths; ensure abstracted volumes do not significantly compromise downstream river and lake needs; and, positioned to minimise vulnerability to surrounding land-use activities. * Identification of the most sustainable management option, e.g., community Water User Associations or parastatal Water Board. * Identification as to whether gravity-fed supply schemes should deliver to households and thereby qualify for a 'Safely Managed', rather than 'Basic' SDG level of service for drinking water supply, the latter being maximum possible for community hand-pumps or taps [62]. * Recognition that easier access to water causes per capita water use to rise--such increases should be weighed against other water demands, sensitive lake-environment needs and changes in water availability due to climate change, agricultural demands, and land-use practices.
## 3 Results and Discussions
### Question Analysis
#### 3.3.3 Available Evidence and Context (RQ4 e RQ5)  
Table 12 presents the distribution of studies according to the levels of evidence described in Table 5 also grouping by the context of application of the studies (academic or industrial). Data extraction was performed based on the items in the form presented in Table 4 to answer questions RQ4 and RQ5 in order to investigate the maturity of the selected studies.  
Based on the distribution presented, it can be seen that most of the selected studies presented some evidence, except for only 10 studies. Among the selected papers, 12 works performed only demonstrations (application descriptions) or examples of use in which 11 were in the academic context and only 1 in the institutional context.  
Considering experiments in laboratories, 28 studies used artificial data in real experiments, in which 23 were in academic context and 5 in institutional context. It should be added that there were no papers that provided expert observations such as textual, qualitative or opinion evaluations.  
Figure 5: Quantitative distribution of studies by support mechanism category and application class.  
For empirical investigations that act on the behavior of approaches within real contexts, 17 works were identified in which, because the context is real, were applied in institutional contexts only. Finally, four studies that performed more rigorous analysis/methodologies of evaluation or validation were identified, all in institutional context.  
In general, we can see that there was a lower tendency for works to be explored in industrial contexts (only 27 studies), although in this study industrial context approaches were also considered, which used industrial data (with appropriate adaptations) and were not necessarily applied within an institution.  
Possible reasons may be that it is difficult to find motivated industry participants to conduct experiments, as well as the fact that conducting controlled experiments requires an excessive amount of effort and resources mainly because much of the information used is classified.