esa-sceva/satcom-chunk-collection huggingface dataset:
# Interactive Part Segmentation Using Edge Images
## 5 Results
### Comparison of Estimated Mask from IOG Model and the Proposed Model  
When segmenting a part with the IOG model, the boundary of the estimated mask is similar to the boundary of the object; on the other hand, when segmenting a part with the proposed model that trained object segmentation with the edge image, the boundary of the estimated mask is similar to the boundary of the part. Table 9 compares each estimated mask obtained from the IOG model and the proposed model. The images of each table have large parts to segment. Looking at the train results in Table 9, in the case of the IOG model, the boundary of the estimated mask is similar to the boundary of the train, but in the case of the proposed model, the boundary of the estimated mask is similar to the boundary of the edge inside the train, which is similar to the boundary of the part. Although there is noise in the area to segment the part in the car of Table 9, the boundary of the estimated mask evaluated from the proposed model is similar to the boundary of the edge with noise. It can be seen that the boundary of the estimated mask from the proposed model, which trained only object segmentation without training part segmentation, is relatively accurate with the boundary of the part.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Model**} & \multirow{2}{*}{**Input Image**} & **Object IOU** & \multirow{2}{*}{**mIOU**} \\  & & **Accuracy** & \\ \hline IOG & Color & 93.2\% & 56.7\% \\  & DexlNed & & \\ Proposed & layer 3 edge & 88.1\% & 60.2\% \\ model 1 & image & & \\  & DexlNed & & \\ Proposed & layer 3 edge & 90.1\% & 59.0\% \\ model 2 & image & & \\ \hline \hline \end{tabular}
\end{table}
Table 7: The IOU accuracy of object and part segmentation for each interactive segmentation model.  
\begin{table}
\begin{tabular}{l c c c c c c c c c c c c c c c c c c} \hline \hline  & **Airplane** & **Bike** & **Bird** & **Bottle** & **Bus** & **Car** & **Cat** & **Cow** & **Dog** & **Horse** & **Motor Bike** & **Person** & **Plant** & **Sheep** & **Train** & **TV** & **Avg.** \\ \hline
**GMNET** & 48.0 & 46.2 & 39.3 & 56.0 & 37.0 & 45.3 & 52.6 & 50.6 & 52.0 & 51.5 & 24.8 & 52.6 & 56.0 & 40.1 & 21.6 & 70.7 & 46.5 \\
**IOG** & 60.9 & 70.0 & 54.4 & _69.7_ & 67.4 & 63.5 & 63.2 & 55.3 & 63.7 & 56.0 & 67.5 & 49.2 & 71.9 & 51.5 & 65.1 & 83.2 & 63.3 \\
**Proposed** & 60.0 & 66.1 & 56.5 & 66.8 & 64.4 & 61.3 & 64.6 & 57.6 & 64.0 & 57.9 & 65.5 & 54.1 & 67.2 & 55.0 & 62.6 & 80.4 & 62.8 \\
**Model 1** & 61.0 & 71.1 & 57.6 & 68.7 & 67.0 & 64.2 & 66.1 & 58.7 & 65.5 & 59.0 & 68.6 & 54.7 & 69.3 & 55.9 & 65.6 & 83.1 & 64.8 \\ \hline \hline \end{tabular}
\end{table}
Table 8: The IOU accuracy of the part segmentation for each object class.
# Review of CMOS Integrated Circuit Technologies for High-Speed Photo-Detection
## 5 Bandwidth Extension Techniques
### Inductive Peaking
The fabrication in 28-nm CMOS technology is provided in [85], and it was reported that the overall chip area reduced by 56% in addition to a power saving of 27% as compared to the fabricated prototype chip with the conventional inductive peaking. Since the on-chip inductor occupies a large area in ICs, the shared inductor is a notable circuit technique because it can significantly reduce the chip area occupied by inductors.
## 5 Discussion and Future Research Directions
### Pricing  
Pricing is a crucial challenge for the service provisioning in the NV environment because it impacts the infrastructure providers' revenues and provides many possibilities for the tenants to maximize their resources leasing by maintaining the lowest price. The majority of the proposed GT solution for the NV exploited the pricing algorithms to overcome resource leasing in multi-tenant environments.
# CONE: A Connected Dominating Set-Based Flooding Protocol for Wireless Sensor Networks
## 3 Design and Implementation of CONE
### Connected Dominating Set Construction  
Based on the centralized tree growing algorithm from [20], we design a distributed algorithm that works in WSNs. The algorithm constructs a DS and then adds nodes to the DS in order to connect the DS. For performing the DS construction, nodes have to know their 1-hop neighbors and their degrees. The degree of a node is defined as the number of a node's known neighbors. In Section 3.2, we describe how nodes discover their neighbors and their degree. Then, we explain the DS construction in Section 3.2.1 and the DS connection in Section 3.2.2.  
Our design does not assume any knowledge of the network topology due to a possibly large network size and random deployment of nodes in an area. For this reason, our algorithm uses only broadcasting for communication. Furthermore, CONE uses event timers and callback timers to randomly schedule transmission in order to reduce duty cycles and packet loss of nodes during CDS construction. An event timer sets a flag to true when it expires. If a callback timer expires, then it triggers a callback function.
## 2 Materials and Methods  
### Study Site, Instrumentation and Data Sources  
The DNP, covering 53,700 ha, is a UNESCO Biosphere Reserve and Natural Heritage and a Ramsar Site, located in the southwest of the Iberian Peninsula. It includes the Donana Biological Reserve (DBR) of 6109 ha (Figure 1a), a core conservation area where ICTS-DBR has established a scientific infrastructure providing long-term monitoring data and access to the scientific community. Figure 1b shows the climogram of the area on a monthly scale. It shows the accumulated precipitation as well as the averages of maximum, minimum and mean temperatures. The average annual precipitation is 548.6 mm and the average annual temperature is 18.4 \({}^{\circ}\)C, based on data from the DBR meteorological stations. However, there is a large interannual and seasonal variability in precipitation and temperature, which affects the hydrological and ecological dynamics of the Donana ecosystems. Different ecosystems are represented in the DBR, such as lagoons, dunes, marshes, shrub areas or forest areas of pine, juniper, or cork oak. The morphology of the area definestwo distinct soil zones: sand (littoral and aeolian systems) and mud-clay (estuarine system) [37]. Our study focuses on two Donana ecosystems: xeric Mediterranean scrub on sandy soils and seasonal marsh on mud-clay soils (Figure 1a), two ecosystems with opposite water dependencies but close enough to be exposed to the same climatic conditions. In this study, similar time frames were chosen depending on the availability of EC data, from July 2019 to December 2022 for xeric shrulands and from October 2020 to December 2022 for marshes.  
The xeric Mediterranean scrub is a semi-arid ecosystem, which represents about 629 ha of the DBR, dominated by xeric shrubs such as _Rosmarinus officinalis_, _Halymium halymifolium_, and _Halymium commutatum_, growing on sandy soils with low organic matter and with functional traits for drought [38; 39]. The Donana marsh is a seasonal wetland that is flooded in winter by rainfall and tributaries, forming an extensive floodplain (537.78 ha in the DBR), mainly dominated by the helpbytes _Bolboschoenus maritimus_, _Schoenoplectus lacustris_, _Juncus subulatus_ and _Arthroenenum macrostachyum_, and the macrophytes _Ranunculus peltatus_, _Rupia drepanensis_, _Chara galiodes_ and _Myriohpyllum alterniflorum_.  
In both ecosystems, the ICTS-DBR installed an EC system (Figure 1a) with a height of 4.75 m for the xeric shrubland (latitude: 37.020206, longitude: \(-6.554403\)) and 3.9 m for the swamp (latitude: 36.998539, longitude: \(-6.434575\)). The sensors and variables used in this study are listed in Table 1.  
Figure 1: (a) Location map of the Donana Biological Reserve (DBR) and the two flux towers. (b) Climogram: average daily precipitation and temperature in the DBR during the study period.  
The remote sensing products used, along with their source, spatial resolution, and number of images, are summarized in Table 2. The products used for this study are described in detail in the following sections.
# Design and Development of Bladeless Vibration-Based Piezoelectric Energy-Harvesting Wind Turbine
## 5 Experimental Results
The angle of the mast was adjusted to be 5 degrees, and experimental work was carried out to investigate the effect of the mast angle of attack on the attainable power. Figure A5 reports the experimentally harvested voltage and voltage readings using the piezoelectric sensor located at the top of the mast, at different wind speeds at a mast angle of 5 degrees, meaning the mast deviates by 5 degrees from the flow stream. Figure A6 reports the experimentally harvested voltage using the piezoelectric sensor located at the middle of the mast with a mast angle of 5 degrees. Figure A7 reports the experimentally harvested voltage using the piezoelectric sensor located at the bottom of the mast with a mast angle of 5 degrees. Figure A8 displays the harvested voltage of all simple cylinders using sensors located at the mast's top, middle, and bottom with a mast angle of 5 degrees. Figure A8 clearly shows that a complex cylinder design with the piezoelectric sensor placed at the bottom of the mast produced the highest amount of energy. The measured voltages were 64 mV at a wind speed of 25 m/s and 44.9 mV at a wind speed of 20 m/s compared to the other designs at both angles and at all possible locations of the piezoelectric sensors. A simple cylinder design with the piezoelectric sensor placed at the bottom comes in second place, generating 49 mV at a wind speed of 25 m/s and 21 mV at a wind speed of 20 m/s. Therefore, based on the obtained results, it can be concluded that the complex cylinder vortex generator design is more feasible and efficient than the other tested designs. Moreover, the best option for the complex cylinder design configuration turned out to be at a 0-degree angle with the piezoelectric sensor placed at the bottom. There is a slight deviation in the results because the voltage reached 69 mV, while other trials reached maximum values of 64 mV at a 5-degree angle. The full-power harnesses achieved by complex cylinder design are 212 nW at a wind speed of 20 m/s.
# Time Series Prediction of Sea Surface Temperature Based on an Adaptive Graph Learning Neural Model
## 2 Materials and Methods  
### Problem Description  
This paper mainly studies the prediction of sea surface temperature time series data. Since the SST data itself has spatial information, we can divide the SST data set into grid data according to latitude and longitude. Then, we regard the SST data set as a grid data set S composed of multi-variable time series X, where X represents the time series data set under different latitude and longitude, and N represents the number of grids after latitude and longitude division of the data set. For each time series data X, a training window with time step P and a prediction window with time step Q are given. Our purpose is to find a mapping function which could predict the SST sequence Y at the future time according to the SST sequence X at the past time. The X, Y, and the mapping function F are defined as follows:  
\[F(X,\theta)=Y \tag{1}\]  
\[X=\left\{X_{t_{1}},X_{t_{2}},X_{t_{3}},\cdots,X_{t_{p}}\right\} \tag{2}\]  
\[Y=\left\{X_{t_{p+1}},X_{t_{p+2}},X_{t_{p+3}},\cdots,X_{t_{p+Q}}\right\} \tag{3}\]  
where \(X_{t_{1}}\in R_{N}\) represents the temperature value of the time series data at \(t_{i}\) moment, and P and Q represent the length of the historical series and the predicted series, respectively.  
In this paper, \(G=(V,E)\) is used to represent the graph formed on sea surface temperature data, where V is the set of spatial nodes of SST information, E is the set of associated relations between spatial nodes, and N is used to represent the number of spatial nodes in the graph. In addition, A represents the collar matrix of the relation between the spatial nodes V in the graph, specifically expressed as \(A\in R_{N\times N}\) with \(A_{ij}=c>0\) if \(\left(v_{i},v_{j}\right)\in E\) and \(A_{ij}=0\) elsewhere.
# Numerical Simulation of Seakeeping Performance on the Preliminary Design of a Semi-Planing Craft
## 4 Results and Discussion
### Sea State Comparisons
#### 4.2.5. Yawing Motion  
Figure 15a-e displays the speed polar diagrams of yawing motion for different wave heading angles at various sailing speeds under sea states (1-5). The diagrams indicated that when the sea state worsened, yawing motion strengthened considerably for wave angles between 45\({}^{\circ}\) and 90\({}^{\circ}\). This suggests that for all sailing speeds, when the wave heading angle ranged from quartering to beam waves, yawing motion increased as the sea state worsened.  
Figure 15. Speed polar diagrams of yawing motion at various sailing speeds for different heading angles when sea state was (**a**) 1, (**b**) 2, (**c**) 3, (**d**) 4, and (**e**) 5, respectively.  
For all Froude numbers, the resonance of yawing motion was evidently produced at a wave heading angle of 45\({}^{\circ}\), and the yawing motion increased when the Froude number increased. This indicated that for all sailing speeds, yawing motion was strongly affected by quartering seas.
## 4 Conclusions  
1. In the lab-scale SBR for municipal wastewater treatment under low organic matter conditions, adopting multiple anoxic and aerobic processes could enhance simultaneous nitrification and denitrification, and complete nitrification would occur in the final aerobic phase.
2. Treatment of raw wastewater from combined sewerage systems (BOD5 \(<\) 150 mg/L; N-NH4 = 28-30 mg/L) showed an efficiency of organic matter removal of 85-90% and nitrogen removal of 75-80%.
3. For nitrification, the best efficiency was achieved when HRT was 2-4 h and the pH value in SBR in the range from 7.5 to 8.0. The specific nitrification rate under these conditions saw the reactor in the range of 0.18-0.23 kg N\({}_{\mathrm{ox}}\)/kg sludge/d. Overall, this achieving Vietnamese standards for discharge wastewater.
4. For denitrification, optimal HRT was in the range 0.5-2.5 h, which demonstrated a specific denitrification rate in the reactor in the range of 0.35-0.45 kg N\({}_{\mathrm{red}}\)/kg VSS/d.
5. The most efficient reduction of nitrate was 70%, which was achieved if the anoxic phase of the reactor lasts 3-5 h to ensure the ORP reaches optimal conditions, and the F/M ratio of the reactor is from 0.4 to 0.6 g BOD/g VSS/d.
6. Despite the overall positive results, the research should be continued in order to provide stable processes in a wider range of concentration in influent wastewater.  
Conceptualization, T.H.Q. and E.G.; methodology, N.M. and I.G.; software, E.M.; validation, T.H.Q., I.G. and N.M.; formal analysis, T.H.Q.; investigation, T.H.Q.; resources, E.M.; data curation, E.M.; writing--original draft preparation, T.H.Q. and E.G.; writing--review and editing, I.G. and N.M.; visualization, E.M.; supervision, E.G. and N.M.; project administration, N.M.; funding acquisition, I.G. and N.M. All authors have read and agreed to the published version of the manuscript.  
This work was financially supported by the Ministry of Science and Higher Education of Russian Federation (grant # 075-15-2021-686). Tests were carried out using research equipment of the Head Regional Shared Research Facilities of the Moscow State University of Civil Engineering.  
Not applicable.  
A number of persons have made this paper possible by various contributions. The authors thank staffs of Environment Protect Research Center, Danang University and especially student [PERSON] and [PERSON] for extending support to authors in our effort to conduct an experiment in Vietnam. The model of SBR reactor was funded and built by Company Investment and Development environmental technology QD Ltd.  
The authors declare no conflict of interest.
## 4 Simulation and Analysis
### Steady-State Performance Analysis  
In the steady-state study, natural wind velocity data measured at Hokkaido Island, Japan, are randomly selected for the simulation. A wind speed of 300 s was applied to each wind turbine generator, and the results are shown in Figure 18. In this paper, the dynamic performances of all of the wind turbine generators are not shown; only the dynamic performances of WTG1 are presented as a representative for all WTGs. The dynamic performances of WTG 1, such as rotor speed response, the voltage profile at the terminal of the stator winding, active and reactive power output of the PMSG, the DC voltage profile at the DC link circuit, active and reactive power output of the grid-side MMC, and voltage profile at the low voltage side of the step-up transformer (Bus BG1), are presented in Figure 19. The total active power and the reactive power output of the wind farm and voltage profile at Bus B33 are presented in Figure 20. In can be confirmed that the dynamic performances of the WTG under steady-state condition can be clearly analyzed  
Figure 17: Power system model.  
in the detailed model and the average model representation, and good dynamic control performances can clearly be seen. It is clear that the average model has sufficient accuracy for steady-state analysis. Moreover, the computation time of the average model is much shorter than that of the detailed model, as presented in Table 4.
## 4 Test-Bed Implementation Setup  
### Hardware Setup  
In order to present the performance improvements that are incurred with the inclusion of the split hop penalty in the path transmission quality metric, a test-bed is set up within the campus of NED University of Engineering and Technology, which comprises four labs with a maximum lab size of 24 feet \(\times\) 56 feet. The total covered area of the labs where the experiment is conducted is 4896 sq ft or 545.8533 m\({}^{2}\). The testbed is composed of a total of 14 real nodes, complete with power backup on a single board. Each node comprises a raspberry pi 4 model B with 4 GB RAM, 8 GB SD card, a 7-inch touchscreen-enabled LCD mounted on top of the raspberry pi, and a 30,000 mAh rechargeable battery to support both raspberry pi and touch-screen. Each node is pasted with the node's IP address for easy access to Secure Shell (SSH) as the MAC address would not be used directly in any test, and address resolution protocol (ARP) will be used to translate IP addresses to MAC addresses. It is also necessary as the tools required to generate data and collect performance measurements also require IP addresses rather than MAC addresses. The touch-screen is mounted with the help screws onto the board so that ample space is available for heat dissipation for both the touchscreen and raspberry pi.  
Figure 6: Split hop penalty flow-chart for each interface in node.  
The complete node is presented in Figure 7, in which the image is captured from the top; therefore, raspberry pi is hidden as it is mounted below the touchscreen. The node is easy to carry and place anywhere around the campus.
## 4 Material Properties and Test Procedures
### Cyclic Loading Test Procedures  
Assuming a modular frame subjected to a lateral force, an experimental method based on cyclic loading, achieved through gradual and incremental displacements of the upper portion of the column in the lateral direction, was used. The loading schedule was based on KBC2016 [14]; after cyclic loading according to the schedule until reaching a drift angle of 0.04 rad (lateral displacement = 88.8 mm), as described in Figure 3, the specimen was elongated to 110 mm (0.05 rad), and the test was completed after observation of the deformation. A 1000 kN actuator was used for the loading, and displacement control was applied at a rate of 0.05 mm/s.  
The lower end of the column was connected with a hinge and bolt, as shown in Figure 4. A steel cap was used so that one end of the floor beam of the upper story module and the ceiling beam of the lower story module could be simultaneously supported by a roller end. A displacement transducer was used to measure the displacement at major points, and a strain gauge was used to measure the strain near the connection area.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Coupon ID**} & \multicolumn{2}{c}{**Cross-Sections**} & \multicolumn{1}{c}{**Yield Strength**} & \multicolumn{1}{c}{**Tensile Strength**} & \multirow{2}{*}{**Elongation (\%)**} \\  & \multicolumn{2}{c}{**(_A_) (mm\({}^{2}\))**} & \multicolumn{1}{c}{**(_Fy_) (N/mm\({}^{2}\))**} & \multicolumn{1}{c}{**(_Fu_) (N/mm\({}^{2}\))**} & \\ \hline \multirow{2}{*}{\(\Box\)-125 \(\times\) 125 \(\times\) 9 (SPSR 400)} & (1) & 224.28 & 416 & 506 & 17 \\  & (2) & 223.33 & 425 & 509 & 18 \\  & (1) & 142.50 & 264 & 407 & 31 \\  & (2) & 146.08 & 262 & 404 & 29 \\  & (1) & 201.66 & 270 & 405 & 32 \\  & (2) & 211.82 & 269 & 408 & 31 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Material test results.  
Figure 3: Loading history for the cyclic loading test.
# Magnonic Metamaterials for Spin-Wave Control with Inhomogeneous Dzyaloshinskii-Moriya Interactions
## 3 Micromagnetic Simulations
The micromagnetic simulation for the five different incident angles, \(\theta_{i}=17^{\circ}\), \(41.5^{\circ}\), \(44^{\circ}\), \(51.2^{\circ}\) and \(67^{\circ}\), are displayed in Figure 3b-f. Figure 3b-d correspond to the refraction mode, and Figure 3e,f are the total reflection mode. Vertical dashed lines correspond to the interface at \(x=2000\) nm between medium A (left) and medium B (right). The critical angle observed in our simulation is estimated to be \(\theta_{c}=51.2^{\circ}\) as shown in Figure 3e. It is important to comment that the spin-wave propagation direction is not strictly perpendicular to the spin-wave wavefronts in our simulation. That is to say, it is easy to observe strong anisotropy in the propagation of spin waves. Typically, for in-plane magnetized films, spin waves dynamics are anisotropic. This means that iso-frequencydispersion relation lines (IFDRLs, slices of dispersion relations for particular frequencies) are not circular. Therefore, the group velocity and phase velocities (parallel to the wave-vector) are not parallel to each other, since the group velocity direction should be normal to the IFDRLs [78]. Such an intrinsic anisotropy called spin-wave collimation effect is common in ferromagnetic films with the magnetization fixed in the plane of the film by an external magnetic field or a strong in-plane anisotropy [75; 76; 77]. However, in the present case, the symmetry of the spin-wave dispersion relation is broken due to the presence of DMI, and the wave vector can be shifted from the direction perpendicular to spin-wave wavefronts [70]. This anisotropy decreases with the increasing frequency of the spin-wave but it is still present at the high frequency \(f=100\) GHz assumed in our simulations. Moreover, a lateral shift \(\triangle_{GH}\) of the spin-wave beam is observed at the interface between the reflected and the incident beams, which is called the Goos-H\(\ddot{a}\)nchen (GH) effect. The GH effect for spin-waves was reported in Refs. [75; 76; 77; 78]. Furthermore, detailed investigations elucidating the role of inhomogeneous DMI on the GH shift in the reflection of the spin-wave at the interface were discussed in Ref. [22].