esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Estimated AGB and Mapping  
The study demonstrated that the combination of polarizations from PALSAR-2 L-band and Sentinel-1A C-band provided advantages for AGB estimation in dipterocarp forest with relatively  
Figure 11: Common interaction of SAR L- and C-bands with the forest structure.  
high AGB. The equation that was derived from the multi linear regression resulted from the best combination of PALSAR-2 and Sentinel-1A polarization, which gives the highest correlation value of 0.356, was used to estimate the AGB within the entire study area. The equation is expressed as  
\[\begin{split}\text{AGB (Mg ha}^{-1})=-10.877\text{VH}-13.292\text{(HH }\times\text{HV)}^{1/2}+139.702\text{HH}+\\ 162.287\text{HV}-6.526\text{(HH}\times\text{HV)}+394.502\text{(HH} \times\text{HV)}^{1/2}+238.524\end{split} \tag{4}\]  
By using this equation, AGB within the entire study area has been retrieved and mapped. Figure 12 shows the spatial distribution of AGB in the study area. From the map, the total AGB in about 5.25 million ha of the study area was estimated at 1,821,214,202 Mg over the year 2016. Figure 13 summarizes the distribution of AGB in the study area, represented by histogram of frequency of pixel occurrences. The distribution was found to be normal throughout the entire study area. Further classification was made to the AGB distribution, reported in intervals as shown in Figure 14. More than half of the study area comprised AGB within the range of 300-400 Mg ha\({}^{-1}\). The highest AGB was concentrated mainly in the northern part of Pahang and southern part of Kelantan, where the largest National Park in Peninsula Malaysia is located. High density of AGB occurred also in the northern part of Perak where Royal Belum State Park is located. These forests are virgin and have existed for millions years and are still intact now. Variations are found scattered in other areas where there was a mix between natural virgin and logged over forests. Low density of AGB appeared near the edges of forest areas, which mostly interacted with other land use activities nearby.  
Figure 12: Spatially distributed map of AGB within the study area.
## 3 Feasibility Analysis of IoT Architecture Utilizing LoRa Communications on Mars  
It is proposed that the feasibility of the proposed architecture for exploring Mars using LoRa be evaluated. This will be conducted by analyzing four key aspects in detail: the constellation model and the revisit time of satellites over IoT nodes on the Martian surface, the maximum communication distance between the IoT nodes and the satellites of the constellation, the maximum capacity of messages that each satellite of the constellation can  
Figure 3: Communication models for nodes: (**a**) ItS-IoT and (**b**) DtS-IoT [14].  
process to determine the volume of IoT nodes, and the interplanetary data communications of the IoT nodes. Below is a theoretical description of the evaluation process.
## 5 Results and Discussion
### Effect of Air Flow Rate  
Air flow rate significantly affects several system characteristics. The values are varied from 56 to 112 mol/s, which corresponds to air stoichiometry of 2 to 4. Figure 7a shows that increasing the air flow rate decreases PCFC power output. This is because excess air lowers the fuel cell temperature and reduces hydrogen production from the reforming reaction, as shown in Figure 7b. The results in Figure 7a also show that the turbine power increases with the increase in air flow rate. Although enthalpy change per mole across the turbine slightly drops as air flow rate is increased, the increase in air flow rate causes the power output to increase. On the other hand, power consumption by the air compressor increases as the air flow rate is increased. The net effect is that the system power output drops. Therefore, the overall efficiency also decreases, as shown in Figure 7c. The exergy efficiency also decreases as a result of increased exergy destruction. Because of its higher system efficiency, air stoichiometry of 2 is considered for the following parametric study.  
Figure 6: Case comparison results; (**a**) energy and exergy efficiency and (**b**) net power output.
###### Abstract  
High-resolution stereo and multi-view imagery are used for digital surface model (DSM) derivation over large areas for numerous applications in topography, cartography, geomorphology, and 3D surface modelling. Dense image matching is a key component in 3D reconstruction and mapping, although the 3D reconstruction process encounters difficulties for water surfaces, areas with no texture or with a repetitive pattern appearance in the images, and for very small objects. This study investigates the capabilities and limitations of space-borne very high resolution imagery, specifically Pleiades (0.70 m) and WorldView-3 (0.31 m) imagery, with respect to the automatic point cloud reconstruction of small isolated objects. For this purpose, single buildings, vehicles, and trees were analyzed. The main focus is to quantify their detectability in the photogrammetrically-derived DSMs by estimating their heights as a function of object type and size. The estimated height was investigated with respect to the following parameters: building length and width, vehicle length and width, and tree crown diameter. Manually measured object heights from the oriented images were used as a reference. We demonstrate that the DSM-based estimated height of a single object strongly depends on its size, and we quantify this effect. Starting from very small objects, which are not elevated against their surroundings, and ending with large objects, we obtained a gradual increase of the relative heights. For small vehicles, buildings, and trees (lengths \(<\)7 pixels, crown diameters \(<\)4 pixels), the Pleiades-derived DSM showed less than 20% or none of the actual object's height. For large vehicles, buildings, and trees (lengths \(>\)14 pixels, crown diameters \(>\)7 pixels), the estimated heights were higher than 60% of the real values. In the case of the WorldView-3 derived DSM, the estimated height of small vehicles, buildings, and trees (lengths \(<\)16 pixels, crown diameters \(<\)8 pixels) was less than 50% of their actual height, whereas larger objects (lengths \(>\)33 pixels, crown diameters \(>\)16 pixels) were reconstructed at more than 90% in height.  
Keywords:VHR tri-stereo satellite imagery; digital elevation model; isolated objects; dense image matching +
Footnote †: journal: Sensors
# Semiautomated Statistical Discontinuity Analyses from Scanline Data of Fractured Rock Masses
## 2 Methods and Theoretical Background  
### Data Acquisition Procedure  
The scanline discontinuity sampling method is based on installing a measuring tape (usually 10 to 30 m in length) on a clean and (as much as possible) planar rock face that is large relative to the size and spacing of the discontinuities exposed [14]. Such rock slopes are found on natural outcrops, road cuttings, quarries, open pit mines, and unsupported adits. Locating planar outcrops in the field large enough for scanline mapping can sometimes be difficult and limit the applicability of this method. [PERSON] [14] recommends approx. 150-350 measurements to characterize a homogeneous area of a rock mass. [PERSON] et al. [11] defines 225 as the minimum number of required discontinuity measurements. In order to avoid large errors in calculating the spacing values, the orientation of one single scanline should not deviate more than 20\({}^{\circ}\) from a straight line [14]. If this is not possible due to the irregular outcrop situation, the scanline should be divided into sections. For a representative data acquisition, it is important to align multiple scanlines at different orientations to provide a three-dimensional sampling setup of the discontinuity network and to minimize the orientation sampling bias. Since scanlines are predominantly subhorizontally oriented, combined analyses with measurements from steeply inclined boreholes, if available, can be performed. Orientation and spacing data of boreholes can be gained from acoustic and optical televiewer borehole imaging. By its nature, it has to be mentioned that borehole data do not provide any information concerning the size or trace length of discontinuities. Core logging data are only useful if special sampling and analysis techniques are applied to enable the determination of the true orientation of the discontinuities.  
Concerning the scanline sampling procedure, the scanline tape is visually inspected for each intersection of a discontinuity trace with the tape [14]. In order to avoid unnecessary data processing, it is advantageous to place the tape on the rock face in such a way that the first discontinuity is located at the zero marker point of the tape. Concerning the sampling procedure, each discontinuity trace and its properties intersecting the measuring tape are recorded systematically on a logging sheet (Figure 1). These properties include the intersection distance, dip direction and angle, semi-trace length above and below the scanline, termination above and below, as well as comments. Optionally, additional parameters such as roughness, curvature, mineralization, opening width or strata thickness can be recorded according to proposed empirical classification schemes (e.g., [1,14]). Comments include the type of discontinuity, infillings and coatings based on mineralization. Mandatory for the analyses of the data are measurements of the trend and plunge of the scanline.  
Figure 1: Scanline survey logging sheet (modified after [14]).
# Analytical Solutions for the Propagation of UltraShort and UltraSharp Pulses in Dispersive Media
## 5 Singular Pulses
### Chirped Rectangular Pulses  
One of the methods to combat dispersion in optical communication is to chirp the pulses, and since most pulses in optical communications are rectangular (in fact they are smooth rectangular, see below) it is instructive to investigate, analytically, the dynamics of a chirped rectangular pulse.  
The initial chirped rectangular pulse has the following form:  
\[A(0,t)=A_{0}\exp\Bigl{(}-iqt^{2}\Bigr{)}rect_{1}(t/\theta)=A_{0}\exp\Bigl{(}- iqt^{2}\Bigr{)}[u(-t/\theta+0.5)-u(-t/\theta-0.5)] \tag{30}\]  
Therefore, using (10) and (24), the pulse profile after a distance \(z\) is  
\[A(z>0,t)=\exp\Bigl{(}\tfrac{-iqt^{2}}{2\beta_{2}zq+1}\Bigr{)}\tfrac{A_{0}}{2 \sqrt{1+2\beta_{2}zq}}\Bigl{[}erfc\biggl{(}\tfrac{t-\theta(1+2\beta_{2}zq)/2}{ \sqrt{-2\beta_{2}z(1+2\beta_{2}zq)}}\biggr{)}-erfc\biggl{(}\tfrac{t+\theta(1+2 \beta_{2}zq)/2}{\sqrt{-2\beta_{2}z(1+2\beta_{2}zq)}}\biggr{)}\Bigr{]} \tag{31}\]  
Besides the widening of the pulse's boundaries, the boundaries also move at a constant \"velocity\", i.e., the two boundaries obey the following relationship:  
\[t_{B}=\pm\frac{\theta}{2}(1+2\beta_{2}qz) \tag{32}\]  
Clearly, when \(q\) is positive, the two boundaries collide at a distance:  
\[z_{f}=-1/2\beta_{2}q, \tag{33}\]  
which is independent of the pulse's width \(\theta\). In Figure 8, the propagation of this pulse for both positive and negative \(q\) is presented.  
While the pulse indeed shrinks for negative \(q\), the pulse's minimum width is reached before the distance \(z_{f}\), i.e., Equation (33). However, if the two pulses are combined, i.e., if the initial pulse is  
\[A(z=0,t)=A_{0}\cos\Bigl{(}qt^{2}\Bigr{)}rect_{1}(t/\theta)=A_{0}\cos\Bigl{(} qt^{2}\Bigr{)}[u(-t/\theta+0.5)-u(-t/\theta-0.5)] \tag{34}\]  
then the minimum width occurs exactly at the distance \(z_{f}\). In Figure 9, the temporal dynamics of this pulse is presented, and the point \(z_{f}\) is clearly shown. Clearly, a smoother, i.e., more realistic, pulse will not converge to an infinitely temporally narrow pulse but instead will converge to a finite temporal width.  
Figure 8: Same as Figure 2, but for the intensity (\(|A(t,z)|^{2}\)) of the pulse presented by Equation (31). On the left, \(q=4/\theta^{2}\); and on the right, \(q=-4/\theta^{2}\). The dashed lines correspond to the pulse’s boundaries \(t_{B}=\pm\theta(1+2\beta_{2}qz)/2\).
# LaRaWAN Metering Infrastructure Planning in Smart Cities
## 4 New Proposals and Results
### Node Deployment Based on Real Geospatial Data  
The use of random network scenarios provides general observations and guidance for network planning. The use of these research results is crucial when planning infrastructure for specific realities. Then, infrastructure elements are located based on terrain maps and the distribution of nodes is described in recognized formats such as GeoJSON [46] or GTFS [47]. Using OpenStreetMap [48] data from Python is convenient thanks to an API called Overpass Turbo [49; 50], which can be used to query geospatial data from OpenStreetMap. In general, all elements in the maps are expressed by a set of points, each of which has a single latitude and longitude. These points are called _nodes_ and _roads_, where nodes are single points usually used to mark places such as individual shops. It is, therefore, possible to use OpenStreetMaps data to pre-plan the placement of LoRaWAN network metering nodes and associate them with the location of the energy meter.  
Due to research related to the pilot construction of a wireless data network in the city of Bydgoszcz, the techniques presented in this article were tested in close connection with the aforementioned location. Bydgoszcz is a city located in northern Poland, situated on the Brda and Vistula rivers. It is the eighth-largest city in the country and the capital of the Kuyavian-Pomeranian Voivodeship. As of the latest available data, Bydgoszcz has a population of approximately 330,000 people. In terms of population density, Bydgoszcz is relatively densely populated, with an average density of around 1875 people per square kilometer. Similar studies have been carried out on the example of Paris [51] but these mainly focused on the reliability of the transmission itself, without taking into account how the gateways were deployed (these were distributed evenly, with LoRaWAN nodes clustered around them).  
For this part of the research, the geographical coordinates of shops and retail outlets were downloaded (there are 741 sites in the OpenStreetMaps database). Geographical coordinates were then converted to Cartesian coordinates and the Euclidean metric was used in the application of the K-means algorithm. An area of the city of \(10\times 10\) km was established for the visualization (Figure 7). The white circles indicate the metering nodes and the red triangles indicate the LoRaWAN gateways. A coverage factor of 0.969 was obtained for 4 gateways (Figure 7a) and for 5 gateways--0.996 with SF = 7 (Figure 7b).  
Figure 6: Dependence of the coverage factor on the spreading factor (SF) for different numbers of LoRaWAN gateways.
## 4 Use of the Controller-Driven OppNet Architecture to Manage Congestion
### Buffer Management  
The control layer applies a congestion control mechanism based on buffer management. Besides the congestion policy limiting the number of message copies in the network, the control layer applies a hybrid drop policy.  
The control layer foresees the network congestion (Section 4.3). Based on the predicted congestion, it limits the number of message copies (Section 4.4) and updates the copies left of the queued messages (Section 4.5). Proactively, if this update results in the message having no copies remaining, the message is marked to be deleted by setting the message's flag \(\varphi\) to false. Reactively, in case of buffer overflow, the messages marked to be deleted are dropped. The control layer applies basic drop policies if more buffer space is required. Itfirst applies a _drop-oldest_ policy based on the message's remaining TTL. Next, if necessary, it applies a _drop-head_ policy removing the oldest ones.  
```
1:\(\triangleright\)\(\delta_{l}\), Received directive (\(\delta_{l}=(H_{l},l^{\prime})\))
2:\(\triangleright\)\(l^{\prime}\): The replication limit in the received directive (\(\delta_{l}=(H_{l},l^{\prime})\)).
3:\(\triangleright\)\(g\): A message (\(g=(\mathfrak{a},l,\varrho,\vartheta)\)).
4:\(\triangleright\)\(B\): A buffer to store messages.
5:functionapplyDirectiveToDifferedMessages(\(\delta_{l}\))
6:for all\(g\in B\)do
7:\(l^{\prime\prime}=\frac{l^{\prime\prime}}{2\pi}\)
8:\(g[l]\gets l^{\prime\prime}\)\(\triangleright\) Setting the new rep. limit in the message's field \(l\)
9:\(g[\vartheta]\leftarrow(l^{\prime\prime}<1)\)?\(false:true\)
10:endfor
11:endfunction
```  
**Algorithm 4** Procedure to update the buffered messages with the \(l\) set by a directive.
# Improving Congestion Control of TCP for Constrained IoT Networks
## 4 Preliminary Performance Evaluation
### Issues to be Addressed
#### 4.2.1 Using the Fixed RTO Value for Retransmitted Segments  
Although uIP TCP measures RTT and estimates RTO based on RTT measurements, the estimated RTO is not used for retransmitted segments. Once retransmission is deemed to be necessary, RTO is fixed at 3 s and backs off exponentially with the number of retransmissions.  
Since uIP TCP estimates RTT in time units of 1 s and uses only integer arithmetic operations, a small RTT value is reduced to 0. If RTT measurements keep small, RTO does not exceed 3 s except when the initial large value (16) of RTT mean deviation still has effects on the RTO value at the beginning of a simulation. Hence, the fixed RTO works well. Figure 2a illustrates such a case. When any RDC mechanism is not used, backing off with fixed RTO does not cause many retransmissions because RTT usually remains below 1 s. However, when RTT gets large, using the fixed RTO value may cause lots of retransmissions. Figure 2b shows that, when ContikiMAC is used, RTT fluctuates and many retransmissions occur. In terms of the relation between ContikiMAC and the hidden problem, [PERSON] et al. stated that, since ContikiMAC lacks preamble strobes in advance of frames, it may more often cause the hidden node problem [14]. In grid topologies, the hidden terminal problem gets more prevalent, which explains why many retransmissions occur when ContikiMAC is used. Note that, even though RTO is updated using the estimated RTT, the actual retransmission timer for a retransmitted segment is set using the fixed RTO of 3 s.
# P-Wave Detection Using a Fully Convolutional Neural Network in Electrocardiogram Images
###### Abstract  
Electrocardiogram (ECG) signal analysis is a critical task in diagnosing the presence of any cardiac disorder. There are limited studies on detecting P-waves in various atrial arrhythmias, such as atrial fibrillation (AFIB), atrial flutter, junctional rhythm, and other arrhythmias due to P-wave variability and absence in various cases. Thus, there is a growing need to develop an efficient automated algorithm that annotates a 2D printed version of P-waves in the well-known ECG signal databases for validation purposes. To our knowledge, no one has annotated P-waves in the MIT-BIH atrial fibrillation database. Therefore, it is a challenge to manually annotate P-waves in the MIT-BIH AF database and to develop an automated algorithm to detect the absence and presence of different shapes of P-waves. In this paper, we present the manual annotation of P-waves in the well-known MIT-BIH AF database with the aid of a cardiologist. In addition, we provide an automatic P-wave segmentation for the same database using a fully convolutional neural network model (U-Net). This algorithm works on 2D imagery of printed ECG signals, as this type of imagery is the most commonly used in developing countries. The proposed automatic P-wave detection method obtained an accuracy and sensitivity of 98.56% and 98.78%, respectively, over the first 5 min of the second lead of the MIT-BIH AF database (a total of 8280 beats). Moreover, the proposed method is validated using the well-known automatically and manually annotated QT database (a total of 11,201 and 3194 automatically and manually annotated beats, respectively). This results in accuracies of 98.98 and 98.9%, and sensitivities of 98.97 and 97.24% for the automatically and manually annotated QT databases, respectively. Thus, these results indicate that the proposed automatic method can be used for analyzing long-printed ECG signals on mobile battery-driven devices using only images of the ECG signals, without the need for a cardiologist.  
electrocardiogram; P-wave; atrial disorder; fully convolutional network +
Footnote †: journal: Applied Sciences
# A Multi-Layer Erbium-Doped Air-Hole-Assisted Few-Mode Fiber with Ultra-Low Differential Modal Gain
## 2 Theory and Model
The combination of the refractive index and doping profile design can effectively reduce the DMG between different guided modes and is conducive to the gain equalization of the FM-EDFA. Several intelligent methods have been proposed for the EDF design in both the refractive index and doping profile, including the genetic algorithm (GA) [27; 28], particle swarm optimization (PSO) [29] and gradient descent optimization (GDO) [30]. In this paper, the erbium-ion doping profile of the proposed AH-FM-EDF is optimized under PSO, and the optimal doping radius and the concentrations were obtained under double- and triple layer doping design, which can balance the overlap integral factors of different pump-signal mode groups and is beneficial to the gain equalization. The proposed AH-FM-EDF is composed of a central air hole, an HRI-AC, and cladding, which is illustrated in Figure 1a. With the central air hole, the modal intensity profile is different from the traditional step-index fiber, as shown in Figure 1b, where \(a_{air}=2\) um, \(a_{co}=9\) um, \(n_{co}=1.452\), and \(n_{cl}=1.444\). The central intensity of the LP\({}_{01}\) mode is strongly depressed. All the modes are confined in the HRI-AC and similar normalized intensities can be obtained. Differing from the step-index fiber, the LP\({}_{02}\) is cut off before the LP\({}_{31}\). The first radial order modes (LP\({}_{01}\), LP\({}_{11}\), LP\({}_{21}\), and LP\({}_{31}\)) are supported in the AH-FM-EDF. The effective RI (ERI) of the signal modes in the C-band is illustrated in Figure 1c. As shown in the figure, the minimal value of the ERI difference is higher than \(1\times 10^{-3}\) over the whole C-band. The normalized intensities and ERI of different guided modes have been carried out using COMSOL Multiphysics software. It is verified that the proposed AH-FM-EDF has excellent modal isolation and it relatively avoids the mode coupling in signal amplification.