esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
Underwater Wireless Sensors Networks (UWSNs) use acoustic waves as a communication medium because of the high attenuation to radio and optical waves underwater. However, acoustic signals lack propagation speed as compared to radio or optical waves. In addition, the UWSNs also pose various intrinsic challenges, i.e., frequent node mobility with water currents, high error rate, low bandwidth, long delays, and energy scarcity. Various UWSN routing protocols have been proposed to overcome the above-mentioned challenges. Vector-based routing protocols confine the communication within a virtual pipeline for the sake of directionality and define a fixed pipeline radius between the source node and the centerline station. Energy-Scaled and Expanded Vector-Based Forwarding (ESEVBF) protocol limits the number of duplicate packets by expanding the holding time according to the propagation delay, and thus reduces the energy consumption via the remaining energy of Potential Forwarding Nodes (PFNs) at the first hop. The holding time mechanism of ESEVBF is restricted only to the first-hop PFNs of the source node. The protocol fails when there is a void or energy hole at the second hop, affecting the reliability of the system. Our proposed protocol, Extended Energy-Scaled and Expanded Vector-Based Forwarding Protocol (EESEVBF), exploits the holding time mechanism to suppress duplicate packets. Moreover, the proposed protocol tackles the hidden terminal problem due to which a reasonable reduction in duplicate packets initiated by the reproducing nodes occurs. The holding time is calculated based on the following four parameters: (i) the distance from the boundary of the transmission area relative to the PFNs' inverse energy at the 1 st and 2 nd hop, (ii) distance from the virtual pipeline, (iii) distance from the source to the PFN at the second hop, and (iv) distance from the first-hop PFN to its destination. Therefore, the proposed protocol stretches the holding time difference based on two hops, resulting in lower energy consumption, decreased end-to-end delay, and increased packet delivery ratio. The simulation results demonstrate that compared to ESEVBF, our proposed protocol EESEVBF experiences 20.2% lesser delay, approximately 6.66% more energy efficiency, and a further 11.26% reduction in generating redundant packets.  
Underwater Wireless Sensor Networks (UWSNs); Extended Energy-Scaled and Expanded Vector-Based Forwarding (EESEVBF); Potential Forwarding Nodes (PFNs) 2019 19 5557 [FOOTNO
## 3 Results and Discussion
### Porosity  
The pore size distributions measured by mercury porosimetry in mortars with variable carbon nanotube contents are presented in Figure 9. It is therein observed that all mortars exhibited overall comparable pore distribution curves with the main features being (i) the dominant peak at ca.  
Figure 8: Chloride diffusion coefficient for each nano-modified mortar.  
\(6\times 10^{-3}\)\(\upmu\)m, on 6 nm, which is fixed throughout variable nano-inclusion concentrations and is inarguably attributed to intra-nanotube porosity, i.e., the over volume corresponding to the internal open space of the cylindrical multi-walled tubes, and (ii) a pore range of non-consistent peaks up to 0.2 \(\upmu\)m.  
The actual porosity values for each mortar with variable CNT concentration are given in Table 2. It is observed that the total porosity drops with an increasing CNT concentration up to 0.4 wt. %, above which it increases to values even higher than the plain case. This may be due to nanotube entanglement issues at higher nano-inclusion concentrations.  
Additionally, chloride diffusion coefficients of corroded mortars are plotted as a function of respective mortar porosity in Figure 10. An inverse correlation between the two parameters is therein observed, with diffusion coefficients values decreasing with total porosity. This finding can be rationalized upon considering that more porous microstructures can block the rate of chloride penetration inside the testing mortars.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**CNT Content \% wt. of Cement** & **Porosity (\%)** \\ \hline
0 & 16.22 \\
0.2 & 14.64 \\
0.4 & 12.68 \\
0.6 & 19.28 \\
0.8 & 20.57 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Porosity values for nano-modified mortars.  
Figure 9: Pore size distributions of nano-modified mortars.  
Based on the above results, chloride diffusion in the processed mortars appears to be strongly linked with CNT concentration. This is due to a combination of mechanisms, one related to the raise of electric conductivity for CNT concentrations above the percolation threshold [2], the other associated to the fact that CNT addition lowers porosity values in the material. Hence, CNTs affect chloride diffusivity both directly, by affecting electrical transport properties, but also indirectly, by affecting the microstructure.
# Proactive Mission Planning of Unmanned Aerial Vehicle Fleets Used in Offshore Wind Farm Maintenance
Our contribution in this respect consists of the following:  
* A declarative reference model of OWF maintenance logistics enabling the integration of operation vessel routing and scheduling problems with UAV delivery and monitoring mission planning problems;
* Procedures for proactive/reactive cruise planning of vessel mooring to selected WTs, including when service teams disembark and return to the vessel, as well as the use of drones for delivery and monitoring purposes;
* The results of many computer experiments, illustrating the possibility of using the presented approach to generate alternative scenarios of OWF maintenance logistics, as well as its scalability. To sum up, the novelty of the proposed approach entails the presentation of two benefits of adopting a reference model. The first is related to the model's open structure, allowing for its further specification and extension. The second comes down to the possibility of formulating and solving so-called synthesis problems (i.e., as opposed to an analysis--answering the question of what happens when). This allows for answers to the following question to be obtained: what requirements for a fleet of ships, a fleet of UAVs, and technical personnel should be met in a given period of time in order to provide services for an assumed number of WTs? The structure of this study is as follows: Section 2 discusses the related work and determines the research gaps in the literature. Section 3 presents a reference model of maintenance logistics of OWT, in particular a declarative model and a formal (in terms of constraint satisfaction problems) formulation of the problem. The case studies presented in Section 4 cover UAV fleet planning for wind turbine servicing and spare-part distribution. Section 5 sums up the results of the computer experiments for assessing the scalability of the proposed solutions. Directions of future research are suggested in Section 6.
###### Abstract  
Water scarcity is a challenging global risk. Urban wastewater treatment technologies, which utilize processes based on single-stage ultrafiltration (UF) or nanofiltration (NF), have the potential to offer lean-and-green cost-effective solutions. Robustifying the effectiveness of water treatment is a complex multidimensional characteristic problem. In this study, a non-linear Taguchi-type orthogonal-array (OA) sampler is enriched with an emergent stigmergic clustering procedure to conduct the screening/optimization of multiple UF/NF aquametric performance metrics. The stochastic solver employs the Databionic swarm intelligence routine to classify the resulting multi-response dataset. Next, a cluster separation measure, the Davies-Bouldin index, is used to evaluate input and output relationships. The self-organized bionic-classifier data-partition appropriateness is matched for signatures between the emergent stigmergic clustering memberships and the OA factorial vector sequences. To illustrate the proposed methodology, recently-published multi-response multifactorial L\({}_{9}\)(3\({}^{\ddagger}\)) OA-planned experiments from two interesting UF-/NF-membrane processes are examined. In the study, seven UF-membrane process characteristics and six NF-membrane process characteristics are tested (1) in relationship to four controlling factors and (2) to synchronously evaluate individual factorial curvatures. The results are compared with other ordinary clustering methods and their performances are discussed. The unsupervised robust bionic prediction reveals that the permeate flux influences both the UF-/NF-membrane process performances. For the UF process and a three-cluster model, the Davies-Bouldin index was minimized at values of 1.89 and 1.27 for the centroid and medoid centrotypes, respectively. For the NF process and a two-cluster model, the Davies-Bouldin index was minimized for both centrotypes at values close to 0.4, which was fairly close to the self-validation value. The advantage of this proposed data-centric engineering scheme relies on its emergent and self-organized clustering capability, which retraces its appropriateness to the fractional factorial rigid structure and, hence, it may become useful for screening and optimizing small-data wastewater operating conditions.  
Keywords:ultrafitration; nanofiltration; lean and green; Taguchi methods; unsupervised classifier; swarm intelligence; emergence; self-organization; bionic clustering; similarity measure; machine learning +
Footnote †: journal: Applied Sciences
## 1 Introduction
### Global Cruise Trends  
A major part of cruising industry is seasonal, which means that most cruise ships follow the season and shift from one region to another in order to achieve optimal passenger occupancy and offer attractive itineraries to passengers. In order to satisfy passenger demand for exciting itineraries and interesting destinations, cruise ships spend the majority of their time in coastal navigation in areas of high natural, environmental and preservation values. They select the most attractive world destinations and navigate along the most attractive coastlines, many of which are environmentally preserved regions with rich biodiversity and high national importance. The usual cruise industry concept is that cruise ships' operation is regional, and itineraries are repetitive, usually in a circular pattern, with limited durations, offering different port experiences every day.  
The question of cruise routes' sustainability in costal navigation becomes important due to the fact that cruise ships spend the majority of their time in coastal navigation. In addition to that, globally, the cruising industry records high passenger demand, high demand for new cruise ships and a trend in which cruise ships are becoming bigger. The expansion of the cruising industry is related to cruising market expansion and the development of new cruising destinations.  
Figure 1 shows the relation between cruise ships' number and cruise ships' berths. Cruise ship berth in this context represents a bed of any type on a cruise ship [13]. For the period from 2000 to 2020, the relation between the passenger movement trend (+5.5%) and the cruise ships' berths trend (+4.7%) indicates a higher cruise ships' occupancy rate. On the other hand, the relation between cruise ships' number trend (+4.1%) and cruise ships' passenger movement trend (+5.5%) shows that cruise ships are becoming bigger. Predictions from the 2020 to 2027 period estimate that the number of cruise ships will grow at an average rate of 2.48% and the cruise ships' berths will grow at an average rate of 3.67% [10; 13]. Growing trends will slightly stabilize, but they still indicate the delivery of larger cruise ships on the market in order to accommodate high passenger demand.  
These factors predict further cruise industry development and cruise traffic expansion. In order to satisfy the demand of the cruise market, it is predicted that popular cruising destinations which are close to reaching their full capacity will maintain the present status or even adjust it, while less prominent cruising regions will continue to grow. It is expected that future cruise industry expansion will focus on new regions that have never been cruising destinations before.
# Precipitation-Use Efficiency and Its Conversion with Climate Types in Mainland China
## 3 Results
### Spatial Distribution and Temporal Variation in PUE  
The distribution of the multiyear average PUE presents a \"low-high-low\" band from northwest to southeast (Figure 9). PUE is relatively low in arid and humid regions and is the lowest in extremely arid and extremely humid regions. The transition zone exhibited the highest PUE. PUE reached its highest value of 2.2 g\(\cdot\)m\({}^{-2}\)\(\cdot\)mm\({}^{-1}\) in the area where the annual precipitation was 414 mm. The regional differences in PUE distribution are closely related to the regional topography, landform, and water expenditure modes. Arid regions have sparse precipitation, sufficient energy, and low and sparse vegetation, and water is  
Figure 8: NPP trend (1960–2017) and (**a**) distribution of average values and trends in sub regions and (**b**) +indicates that the trend was significant at the 0.05 level.  
Figure 7: Comparison of estimated NPP and MOD17A3 NPP (average values from 2000 to 2017).  
mostly spent in the form of soil evaporation. Therefore, vegetation PUE is low. Humid regions have abundant precipitation, but there are many rainstorms of large intensity [76]. Precipitation is dissipated in the form of runoff, canopy interception, and soil evaporation, which may produce more ineffective water. In addition, in the humid region, there are mostly mountainous and hilly land forms with large surface runoff. Hence, PUE is also low there.  
Figure 10 shows the PUE trend in China from 1960 to 2017 and the distribution of average values and trends in the sub regions. Over the past 58 years, PUE in the arid region increased at a rate of 0.014 g\(\cdot\)m\({}^{-2}\cdot\)mm\({}^{-1}\cdot\)10a\({}^{-1}\), indicating that the ability of vegetation in those regions to convert water and nutrients into biomass has increased. PUE in the transition zone was the highest, with an average of 1.92 g\(\cdot\)m\({}^{-2}\cdot\)mm\({}^{-1}\), and generally showed a slight decreasing trend. In the western part of the transition zone (i.e., west of 103\({}^{\circ}\) E), PUE decreases and ecology deteriorates, which is consistent with current grassland degradation in the upper reaches of the Yellow River [77]. In the middle of the transition zone (i.e., between 103 and 120\({}^{\circ}\) E), PUE increases. PUE in the eastern part (i.e., east of 120\({}^{\circ}\) E) decreases. Most of the PUE in the humid region exhibits a decreasing trend of \(-\)0.003 g\(\cdot\)m\({}^{-2}\cdot\)mm\({}^{-1}\cdot\)10 a\({}^{-1}\). In recent years, rainstorm intensity in humid regions has significantly increased, as has the proportion of rainstorms in annual precipitation [76]. Rainstorms are more likely to form runoff. Hence, this change in precipitation intensity is one of the reasons for the PUE decrease in the region.
## 3 Results
### Characteristics of the Amount of Sap Obtained from Individual Trees
#### 3.1.2 Seasonal Birch Sap Leak Efficiency  
In the mixed coniferous forest site, during the entire study period, the total amount of sap obtained was the highest for trees THN3 (315.58 dm\({}^{3}\)) and MED1 (333.38 dm\({}^{3}\)). The lowest seasonal efficiency was characteristic of tree MED2 (88.58 dm\({}^{3}\)). The average value was 176.76 dm\({}^{3}\), the highest value for the compared habitats (Table 2).  
In the mixed broadleaved forest site, the most sap was extracted from tree TCK2--360.61 dm\({}^{3}\)--and the least from tree THN1--22.69 dm\({}^{3}\). The average amount of harvested sap was 147.29 dm\({}^{3}\). In the case of the broadleaved forest site, the highest total amount of leaking sap was found for tree MED3--260.68 dm\({}^{3}\)--and the lowest for tree THN3--35.92 dm\({}^{3}\). The average amount of sap harvested from one tree in the season (124,64 dm\({}^{3}\)) was the lowest of all compared habitats (Table 2). A considerable variation in the total amount of harvested sap was observed between trees growing in the exact location. The highest variability was found in the mixed broadleaved forest site, where the coefficient of variation was 65.05% (Table 2), and the lowest was found in the mixed coniferous forest site (55.27%). From all trees growing in the individual habitats, the following totals were collected (a total for nine trees): mixed coniferous forest--1590.87 dm\({}^{3}\); mixed broadleaved forest--1325.59 dm\({}^{3}\); broadleaved forest--1121.72 dm\({}^{3}\). From all 27 trees in the three distinguished habitats, a total of 4038.17 dm\({}^{3}\) of sap was collected.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline
**Site** & **Number of Trees** & **Average [dm\({}^{3}\)]** & **Minimum [dm\({}^{3}\)]** & **Maximum [dm\({}^{3}\)]** & **Standard Deviation** & **Coefficient of Variation [\%]** \\ \hline Mixed & & & & & & \\ coniferous & 9 & 176.76 & 88.58 & 333.38 & 97.70 & 55.27 \\ forest & & & & & & \\ broadleaved & 9 & 147.29 & 22.69 & 360.61 & 95.81 & 65.05 \\ forest & & & & & & \\ \hline  & & & & & & \\  & & & & & & \\  & & & & & & \\
260.68 & & 72.46 & 58.14 & \\ \hline  & & & & & & \\  & & & & & & \\ \end{tabular}
\end{table}
Table 2: Summary statistics for all-season harvested sap volume (dm\({}^{3}\)/tree).  
Figure 2: Changes in the daily amount of birch sap harvested during the season.
# Ferrite-Loaded Spidron Fractal Loop VHF Antenna for UAV Applications
## 1 Introduction  
VHF/UHF band wireless communication antennas are widely used in unmanned aerial vehicles (UAV) applications, such as air traffic control systems, air navigation systems, and military communication systems. Monopole and dipole types of antennas are most commonly used for UAV applications [1; 2; 3; 4; 5; 6; 7]. However, these antennas have several disadvantages when used in UAV applications, such as size and weight issues. Recently, electrically small antennas (ESAs) for UAV applications have been introduced to remedy these disadvantages [8; 9]. An ESA is defined as an antenna that meets the condition of \(ka<0.5\), where \(k\) is a wavenumber in a free space condition and \(a\) is the radius of an imaginary sphere surrounding the antenna. However, ESAs have low gain levels due to their high radiation \(Q\) (the ratio between the radiated/dissipated energy and the stored energy; \(Q=1/ka+1/(ka)^{3}\)), which is determined only from the \(ka\) value [10; 11].  
One of the techniques by which to solve the low gain problem is through material loading. The gain of the material loaded into the ESA can be improved by lowering the radiation \(Q\) of the ESA, which is determined by the permittivity and permeability of the material [12]. Studies of a material loaded monopole and loop type ESAs have been conducted [13; 14], respectively. The radiation \(Q\) of monopole and dipole types of ESAs operating in the TM10 mode is proportional to the permittivity of the material (\(Q\propto\epsilon\)). It is difficult to increase the antenna gain using a dielectric material loading technique because the permittivity of any dielectric material is higher than the permittivity of free space (\(\epsilon=1\)). For a loop type ESA operating in the TE10 mode, the radiation \(Q\) of the antenna isinversely proportional to the permeability of the material (\(Q\propto 1/\mu\)). Accordingly, the gain of a loop type ESA can be improved by loading a magnetic material with high permeability [12].  
In this letter, a ferrite-loaded electrically small Spidron fractal loop antenna for UAV applications was designed. By applying ferrite to the inside of the loop antenna, the low frequency gain of the loop antenna is improved while the high frequency gain is attenuated due to the loss property of the ferrite. To solve the gain reduction problem, the amount and configuration of the ferrite are optimized by a genetic algorithm (GA). In the following sections, details of the design and performance of the proposed antenna are presented and discussed. The proposed antenna when mounted on a UAV is also examined.
# An Ontology-Based Expert System for Rice Disease Identification and Control Recommendation
## 3 Ontology Development for RiceMan
### Ontology Design and Development
#### 3.2.1 RiceDO and TreatO: Original Design  
RiceDO and TreatO, initially introduced in [14], model terminological knowledge with classes and properties related to traits and phenotype of various rice diseases in Thailand. Their main objectives are to support retrieval of potential diseases that might occur on a rice plant, given an expression of abnormal characteristics with a DL query language. Supported queries could be either in the form of a single appearance (such as a gray spot) or multiple ones (such as a gray spot with a yellow oval spot). The ontologies cover 22 rice diseases and paddy insects in Thailand and coincide with the aforementioned CQs. However, the modeled knowledge is verbose and impractical for the disease identification and control recommendation. To overcome these issues, we further investigate and redesign the ontologies. Thus, incorrect and improper design issues are identified, including (1) unused classes; (2) classes and properties with ungrammatical semantics; (3) classes with semantic overlapping; (4) inappropriateness of class-subclass relationships; and (5) lack of restrictions in domains/ranges of properties.
## 4 Validation Experiments
### Spectrum Sensing  
Once the receiver frequency response was equalized in the initial off-line calibration step, the detection process could take place. Power levels were estimated based on the periodogram (squared magnitude of the FFT of the received signal) [40].  
We used an FFT of length \(N\) = 1,024, with the possibility of averaging the periodograms over \(P\geq 1\) blocks. The estimated power level in channel \(n\) is given by averaging all the bins within the channel, _i.e._,  
\[PL_{n}=\frac{1}{N_{n}P}\sum_{p=1}^{P}\sum_{k\in A(n)}|X_{p}(k)|^{2} \tag{1}\]  
where \(Xp(k)\) denotes the \(N\)-point FFT of the \(p\)-th block, \(A(n)\) is the set of frequency bins corresponding to channel \(n\), and \(N_{n}\) is the cardinality of \(A(n)\). Let the sensing time for a 3-MHz subband be \(T_{sensing}=N\cdot P/fs\). Then, the total time to scan the whole 25-MHz bandwidth of the GSM900 downlink is  
\[T=\lceil\frac{25}{3}\rceil(T_{sensing}+T_{settling}) \tag{2}\]  
where \(T_{settling}\) is the settling time after the center frequency changes (milliseconds in our case). In spectrum sensing systems, the decision about the status (busy/idle) of a given downlink channel depends on the background noise level (NL) reference, which degrades performance randomly [41]. In order to overcome this problem, since some downlink channels were always idle, we estimated the NL as the lowest power level across all channels of the GSM900 downlink. The corresponding channel was automatically tagged as idle. The remaining channels were subject to statistical hypothesis tests, according to which channel \(n\) was busy if the ratio of the estimated power level \(PL_{n}\) in that channel to the estimated NL exceeded a threshold.  
The threshold was set for sufficiently small probabilities of false alarm (\(P_{FA}\)) and missed detection (\(P_{MD}\)) for signals that exceeded the NL by 9 dB (remember that this is the minimum \(C/I\) level required for GSM communications [42]). Assuming that the measured power levels follow a Gaussian distribution and that the background noise is Gaussian and uniform across the whole bandwidth, \(P_{FA}\) and \(P_{MD}\) can be derived in closed form.  
Figure 15 plots these levels as a function of the threshold for \(C/I\) = 3 dB and for different values of \(P\). It shows how \(P\) = 5 blocks sufficed to set a threshold that simultaneously achieved \(P_{FA}\) = \(10^{-6}\) and \(P_{MD}\) = \(10^{-6}\). Note that a failed detection resulted in a missed carrier, whereas a false positive meant that an empty channel was misidentified as busy. With \(P\) = 5, the whole 25-MHz bandwidth was scanned in less than 0.5 seconds.