esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results
After the pressure increase, several days were required to achieve the steady-state diffusion for a higher pressure. After that time, the measured concentration became stable again on a higher level. According to the Equations (3) and (4), increases of the pressure and permeability coefficient are linear. Pressure was raised by 70%, which gave the increase of measured concentrations by more than 60% as well (after achieving steady-state diffusion). This confirmed that the measuring methodology was correct. Slightly lower increase in concentration, in comparison with the pressure increase, may be explained by higher confining pressure (double the gas pressure, which was approx. 3.6 MPa). It can cause a compaction of the sample, which caused a slight decrease of the permeability. This phenomenon was described for concrete samples in [19], as well as for the polymer materials, where hydrostatic compression effect occurs [15]. However, the scale of permeability decreased, as well as mechanism responsible for it, is different. To compare the gas permeability results of different materials with the microstructure of the samples, SEM imaging of selected samples was done. Structures of the samples are shown in Figure 4. An evident difference is seen in microporous and plain materials. Dark areas representing pores are clearly visible in concrete and mudstone samples under similar magnification (Figure 4a,b). In the plain samples, voids appear mostly on the contact surface with grains of additives (Figure 4e). Figure 3: Increase of hydrogen concentration during the Carrier Gas Method test of epoxy resin with fly ash (30% vol.) with 1.0 MPa and 1.7 MPa feed gas pressure.
# Two-Lane Highways Crest Curve Design. The Case Study of Italian Guidelines
## 1 Introduction  
In highway design, vertical curves have to be used to transition grade changes. Vertical curves should be chosen considering many relevant issues such as driver safety, comfort, alignment aesthetics, and drainage purposes [1; 2; 3; 4]. Vertical curves are of two classes: convex vertical curves, known as crest curves, and concave vertical curves, known as sag curves [5; 6]. Parabolic or circular curves are the common choices for vertical curves both in highway engineering [1; 5; 6] and in railway engineering [7; 8]. Generally, parabolic curves are preferred, because they provide a constant rate of curvature change [6; 9].  
The main purpose of a crest curve's design is to calculate the minimum vertical curve radius (R\({}_{\rm v,min}\)) that complies the required sight distance (stopping sight distance SSD or passing sight distance PSD), according to total grade change \(\Delta\)i, design speed v, and drivers' comfort. As it is well known, too short a vertical curve radius may lead to insufficient sight distance.  
Safe operation on crest vertical curves mainly depends on ample sight distance. Minimum stopping sight distance SSD should be ensured in all cases [6; 9]. Table 1 shows the minimum radii of crest vertical curves as a function of design speed in various countries [6]. Wherever economically and technically feasible, passing sight distance PSD should be provided on two-lane highways [6; 9].  
In this article, the relationship between crest vertical curve radius R\({}_{\rm v}\), passing sight distance PSD, driver eye height h\({}_{1}\), object (i.e., opposing vehicle) height h\({}_{2}\), and the characteristics of vehicle was obtained, considering for h\({}_{2}\) not a conventional value (i.e., h\({}_{2}\) = 1.10 m in the case of the Italian guidelines [10; 11]) but the real vehicle heights. This is because, in recent decades, there has been a generalized significant increase in the vehicles' height. For example, the roof top height of modern sportutility vehicles (SUVs) is often more than 1.70 m. Therefore, in order to evaluate a reasonable value for h\({}_{2}\) a statistical sampling of the height of vehicles circulating in Italy was carried out. In particular, the average vehicle heights h\({}_{2(\text{m})}\) and the value of the 15 th percentile of the height distribution h\({}_{2(15)}\) have been calculated.  
A comparative analysis between the vertical convex curves radii recommended in the Italian Guidelines for the Design of Road Infrastructures (h\({}_{2}\) = 1.10 m) [10] and the homologous values calculated with the analytical relationships proposed in this research (based on h\({}_{2(\text{m})}\) and h\({}_{2(15)}\) parameters) was developed.  
The results show that the h\({}_{2}\) value prescribed by the Italian guidelines [10; 11] (h\({}_{2}\) = 1.10 m) is excessively precautionary, since it results in h\({}_{2(\text{m})}\) = 1.48 m and h\({}_{2(15)}\) = 1.39 m, respectively. It follows the oversizing of the radius of vertical convex curves and their length, with consequent greater highways construction costs.
## 3 Experimental Section
### Batch Adsorption Experiments  
All the adsorption experiments were carried out on a rotary shaker at 150 rpm. Fixed dose (0.05 g) of adsorbent was added into 50 mL of a solution of known Cr(VI) concentration in 250 mL flasks, and then the flasks were agitated to reach the adsorption equilibrium. Then the residual concentration of Cr(VI) was analyzed inductively coupled plasma (ICP) spectrophotometry (PE Optima 8000, Waltham, MA, USA). To investigate the effect of pH, 50 mL of 300 mg/L Cr(VI) solutions with various initial pH at 1-8 was carried out at 298 K. The pH value was adjusted by 1 mol/L NaOH or 1 mol/L HCl. Effects of sorption time and sorption kinetics experiment were investigated at an initial pH of 2.0 by measuring the adsorption amount at different time intervals. 0.05 g EDA-MPMs was added to 50 mL of Cr(VI) aqueous solutions with concentration (100, 200 and 300 mg/L) at different temperature.  
Adsorption isotherm was measured by contacting 0.05 g EDA-MPMs microbeads with 50 mL of Cr(VI) aqueous solutions at different initial concentration (100, 150, 200, 300, 400, 600, 800 and 1000 mg/L) shaking for 8 h. The experiments were performed at three different temperatures (298, 308 and 318 K). The equilibrium adsorption capacity (\(q_{e}\)) was calculated by Equation (1):  
\[q_{e}=\frac{(c_{0}-c_{e})V}{m} \tag{10}\]  
where \(c_{0}\) and \(c_{e}\) represent the initial and equilibrium Cr(VI) concentrations in solution (mg/L), respectively; \(V\) is the volume of solution (L) and \(m\) is the amount of adsorbent (g).
# Diverse Feature-Level Guidance Adjustments for Unsupervised Domain Adapative Object Detection
## 4 Experiments
### Comparative Experiments
#### 4.3.2 Cross-Camera Adaptation  
To validate the effectiveness of our method, experiments were conducted, not only for weather differences in paired datasets, but also for adapting to camera distinctions, using the Cityscapes [39] and KITTI [40] datasets, as presented in Table 2. We utilized these datasets as the inputs for the source and target domains, respectively. According to Table 2, DFGAs achieved 59.5% mAP and 87.6% mAP in detecting cars. In comparison with TIA, DFGAs achieved improvements of approximately 15.5% mAP in KITTI \(\rightarrow\) City and 11.7% mAP in City \(\rightarrow\) KITTI. It is evident that our method exhibited remarkable performances when mitigating the domain shift arising from camera differences.  
\begin{table}
\begin{tabular}{l c c c c c c c c c} \hline \hline
**Method** & **Bus** & **Bicycle** & **Car** & **Mcycle** & **Person** & **Rider** & **Train** & **Truck** & **mAP** \\ \hline Faster R-CNN & 25.5 & 30.3 & 34.2 & 19.0 & 25.1 & 33.4 & 9.1 & 12.1 & 23.7 \\ DA Faster R-CNN & 35.3 & 27.1 & 40.5 & 20.0 & 25.0 & 31.0 & 20.2 & 22.1 & 27.6 \\ SDWA & 36.2 & 35.3 & 43.5 & 30.0 & 29.9 & 42.3 & 32.6 & 24.5 & 34.3 \\ ATF & 43.3 & 38.8 & 50.0 & 33.4 & 34.6 & 47.0 & 38.7 & 23.7 & 38.7 \\ SAP & 46.8 & 40.7 & **59.8** & 30.4 & **40.8** & 46.7 & 37.5 & 24.3 & 40.9 \\ MeGA & 49.2 & 39.0 & 52.4 & 34.5 & 37.7 & **49.0** & 46.9 & 25.4 & 42.8 \\ TIA & 52.1 & 38.1 & 49.7 & 37.7 & 34.8 & 46.3 & **48.6** & 31.1 & 42.3 \\ \hline
**Ours** & **53.6** & **41.6** & 53.0 & **40.1** & 36.8 & 47.9 & 41.3 & **34.3** & **43.6** \\ \hline \hline \end{tabular}
\end{table}
Table 1: Experimental results (%) of DFGAs method on the Cityscapes \(\rightarrow\) Foggy Cityscapes compared with other methods.
# Generalized Frequency Division Multiplexing-Based Low-Power Underwater Acoustic Image Transceiver
###### Abstract
[20] proposed a UWA multimedia communication scheme with 2400 transmission modes to combat the time-varying multipath UWA channel environment. The orthogonal variable spreading factor scheme, gold sequence scramble code, direct mapping (DM), or space-time block code multi-input multi-output (MIMO) transmission strategy, OFDM, BPSK, or quadrature phase-shift keying adaptive modulation, a convolution channel code with rates of 1/2 and 1/3, and a power assignment mechanism, were integrated into the proposed UW OFDM-based system. [PERSON] et al. [21] developed the filterbank multicarrier (FBMC) technique in doubly dispersive UWA communication channels, and a filterbank prototype filter with a novel cost optimization function to achieve robust signal-to-interference-plus-noise ratios and BER performances. [PERSON] et al. [22; 23] explored an FBMC-based UWA multimedia communication scheme incorporating single-input single-output (SISO) and DM MIMO transmission mechanisms, (2000, 1000) low-density parity-check (LDPC) encoders, adaptive BPSK or offset quadrature amplitude modulations, and a power assignment method. [PERSON] et al. [24] proposed a filtered multitone (FMT) modulation-based UWA transmission system with low-complexity channel-estimation (CE)-based minimum mean square error (MMSE) turbo equalization, and evaluated the symbol error rate (SER) performances. Simulation results show better transmission performance with higher throughput than the FMT modulation UWA transmission with traditional MMSE adaptive equalization. [PERSON] et al. [25] evaluated the performance of a GFDM transceiver in a high-data-rate UWA transmission channel in terms of the spectral efficiency, peak-to-average power ratio, SER, and complexity of the proposed GFDM transceiver. [PERSON] et al. [26] analyzed the peak-to-average power ratio (PAPR) performance of a GFDM system with a pulse-shaping filter, and compared it with that of the OFDM. [PERSON] et al. [27] developed a non-orthogonal multicarrier scheme, GFDM, for reliable and efficient underwater transmission systems, and evaluated its BER performance in additive white Gaussian noise (AWGN) and Rayleigh fading UW channels. The advantages of a GFDM physical layer design, such as low transmission BER performance, low computational complexity, and less bandwidth overhead, make GFDM a suitable transmission scheme in underwater communication. The remainder of this paper is organized as follows: In Section 2, the proposed GFDM-based UWA image transmission technology is briefly described. In Section 3, the simulation results of the proposed transceiver are presented and the underwater image transmission scheme performance is evaluated in detail. Finally, the conclusions are presented in Section 4.
# Real-Time Geo-Localization for Land Vehicles Using LIV-SLAM and Referenced Satellite Imagery
## 4 Experiments
### Adaptability Evaluation  
Significant scene variations and transitions into indoor environments may cause substantial discrepancies between real-time projection images and referenced images, thereby greatly reducing the reliability of image matching. To address this issue, two strategies can be adopted. First, enlarging the projection image area can help include more corresponding features, thus improving matching robustness. Figure 7 presents an example of indoor environment, where the red cross represents the current localization, Figure 7a,b show the projection image of the local region and its corresponding reference map, respectively. Compared to the 100 m \(\times\) 100 m projection image, the 150 m \(\times\) 150 m projection image includes a larger portion of the surrounding outdoor area, thereby capturing more features that effectively correspond to the reference image. Additionally, increasing the search range allows the matching algorithm to relocate the correct position after passing through disturbed or occluded regions.  
Although the correct position can be relocated by increasing the search range, the fused localization accuracy will be still degraded due to the incorrect matching results. To mitigate this, the proposed OAGS mechanism adaptively adjusts the Kalman gain based on the matching confidence, thereby significantly suppressing the adverse impact of incorrect observations. As illustrated in Figure 8a, erroneous observations from image matching could lead to significant localization errors, while Figure 8b shows the result after applying the proposed OAGS mechanism. By effectively suppressing unreliable observations during indoor environments, the fusion trajectory with OAGS remains significantly closer to the ground truth, indicating a clear improvement in both localization robustness and accuracy.  
Figure 7: Comparison of using different projection sizes. **(a)** Projection image with different size; **(b)** The corresponding referenced image.
## Materials and Methods
### Methods  
#### 2.4.1 Spectral Index Detection of Changes in Plant Status Across GSD and Time  
Each geometrically and radiometrically calibrated orthomosaic was left at its native resolution, as NDVI and NDRE were calculated from the multispectral bands. The values for all pixels within the delineated boundaries of the treatment and control canopies were averaged, to provide a mean value for each treatment block at each time period/flight. The pixels within the entire study area, formed by a bounding box of the treatment and control areas were also averaged. We plotted the average NDVI and NDRE across each ground sample distance (GSD) that correspond to the varying altitude at which the UAV was flown (Figure 2). Further, using all flights flown on Day 2 at 60 m altitude (4.3 cm GSD), we plotted the average NDVI and NDRE values for each treatment, flown every hour from 8 am to 3 pm (n = 8) (Figure 2).  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Flight** & **Date** & **Time** & **Altitude** & **GSD RedEdge (cm)** \\ \hline F1 & 25 July 2018 & 12:00 & 120m & 8.81 \\ \hline F2 & 25 July 2018 & 13:15 & 100m & 7.29 \\ \hline F3 & 25 July 2018 & 14:10 & 30m & 2.26 \\ \hline F4 & 25 July 2018 & 15:10 & 60m & 4.45 \\ \hline F5 & 26 July 2018 & 08:17 & 60m & 4.47 \\ \hline F6 & 26 July 2018 & 09:32 & 60m & 4.42 \\ \hline F7 & 26 July 2018 & 10:13 & 60m & 4.48 \\ \hline F8 & 26 July 2018 & 11:10 & 60m & 4.49 \\ \hline F9 & 26 July 2018 & 12:10 & 60m & 4.71 \\ \hline F10 & 26 July 2018 & 13:24 & 60m & 4.42 \\ \hline F11 & 26 July 2018 & 14:10 & 60m & 4.40 \\ \hline F12 & 26 July 2018 & 15:10 & 60m & 4.36 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Overview of UAV (unmanned aerial vehicles) flights flown on 25 July 2018 and 26 July 2018 with a MicaSense RedEdge multispectral camera at varying times and ground sampling distances (GSDs).
# A Novel Fault-Tolerant Aware Task Scheduler Using Deep Reinforcement Learning in Cloud Computing
## 5 Simulation and Results
### Calculation of Energy Consumption for DRFTSA Using Regular Dataset by Varying Number of VMs  
In this section, we present the next scenario of the generated energy consumption for DRFTSA with a regular dataset and by using various numbers of VMs. We considered VMs linearly by changing them and assigning them to various tasks, i.e., for 100, 200, 300, 400, 500, 600 tasks by 10, 20, 30, 40, 50, 60 VMs, respectively. The proposed DRFTSA was compared to existing PSO, GA, and ACO algorithms to check the efficacy of DRFTSA. Generated energy consumption for PSO with 100, 200, 300, 400, 500, 600 tasks is 63.25, 65.72, 68.16, 72.76, 77.95, 82.56, respectively. Generated energy consumption for GA with 100, 200, 300, 400, 500, 600 tasks is 67.03, 68.87, 71.46, 72.52, 76.88, 81.64, respectively.  
Generated energy consumption for ACO with 100, 200, 300, 400, 500, 600 tasks is 69.47, 70.58, 73.84, 79.73, 82.81, 83.88, respectively. Generated energy consumption for DRFTSA with 100, 200, 300, 400, 500, 600 tasks is 54.99, 57.18, 62.18, 64.86, 66.71, 72.13, respectively. From Table 9 and Figure 9, it is evident that energy consumption of DRFTSA compared to various approaches is greatly minimized with the considered dataset and VMs.
# Evaluation of IMERG Precipitation Products in the Southeast Costal Urban Region of China
## 1 Introduction
These previous efforts were large-scale regional assessments, with little focus on urban areas where accurate, timely and high-resolution precipitation information is urgently needed for urban management, disaster warning and policy development. In order to take full advantage of the fine temporal resolution of IMERG, evaluations at sub-daily timescales are needed, with an emphasis on how effectively the products can describe sub-daily precipitation. To explore the above issues, this study presents an evaluation of the IMERG precipitation products for the southeast coastal region of China during 2018. The region has a typical coastal urban agglomeration, with a compact infrastructure, dense population, and high economic connectivity. Located along the coast, this urban agglomeration frequently suffers from torrential rains, typhoons, and floods, which pose great threats to human life and the economy. Within the region, a high-density rain gauge network has been established to measure hourly precipitation, providing the opportunity to investigate the sub-daily performance of the IMERG products in coastal urban areas. The main objectives of this study are: (1) to evaluate the overall estimation and detection ability of the IMERG products at multiple temporal scales (hourly and daily); (2) to analyze and compare the IMERG performance in coastal urban and non-urban areas; and (3) to investigate the performance of the IMERG products in different parts of the study area at the grid-scale. This work can provide useful references for research and the application of IMERG precipitation data in the fields of water resources management, development planning and disaster early warning in coastal urban areas.
# Systematic Analysis of Wind Resources for Eolic Potential in Bangladesh
###### Abstract  
Energy consumption in Bangladesh increased for economic, industrial, and digitalization growth. Reductions in conventional sources such as natural gas (54%) and coal (5.6%) are calls to enhance renewable resources. This paper aims to investigate the atmospheric variables for potential wind zones and develop a statistical power-forecasting model. The study-site is Bangladesh, focusing on eight divisions across two regions. First, the southern zone includes Dhaka (Capital), Chittagong, Barishal, and Khulna. The northern regions are Rajshahi, Rangpur, Mymensingh, and Sylhet. This investigation illustrates wind (m/s) speeds at various heights (m) and analyzes the boundary layer height (BLH) from the European Center for Medium Range Weather Forecast reanalysis 5 th generation (ERA5). The data is from a period of 40 years from 1979 to 2018, assessing with a climatic base of 20 years (1979 to 2000). The climatological analysis comprises trends, time series, anomalies, and linear correlations. The results for the wind speed (BLH) indicate that the weakest (lower) and strongest (higher) regions are Sylhet and Barishal, respectively. Based on power-curve relationships, a simple power predictive model (SPPM) is developed using global wind atlas (GWA) data (sample: 1100) to estimate the power density (W/m\({}^{2}\)) and found an accuracy of 0.918 and 0.892 for Exponential (EXP) and Polynomial (PN) with mean absolute percentage errors (MAPE) of 22.92 and 21.8%, respectively. For validation, SPPM also forecasts power incorporating historical observations for Chittagong and obtains correlations of 0.970 and 0.974 for EXP and PN with a MAPE of 10.26 and 7.69% individually. Furthermore, calculations for annual energy production reveal an average megawattage of 1748 and 1070 in the southern and northern regions, with an MAPE of 15.71 and 5.85% for EXP and PN models, except Sylhet. The SPPM's predictability can be improved with observed wind speeds and turbine types. The research wishes to apply SPPM for estimating energy in operational power plants.  
renewable wind energy; wind speeds; boundary layer height; power forecasts; Bangladesh 2021  
[PERSON], [PERSON], S.K.
# Use of SMAP Soil Moisture and Fitting Methods in Improving GPM Estimation in Near Real Time
## 3 Model and Method
### Fitting Correction Methods
#### 3.3.1 Linear Fitting Correction  
The mean bias can be adjusted with the linear correction. The linearly corrected precipitation \(\mathrm{P}_{\mathrm{linear}}\) is simply calculated by the satellite estimates multiplied by the correction factor a  
\[\mathrm{P}_{\mathrm{linear}}(\mathrm{i},\mathrm{t})=\mathrm{a}_{\mathrm{i}} \times\mathrm{P}_{\mathrm{O}}(\mathrm{i},\mathrm{t}), \tag{7}\]  
where \(\mathrm{P}_{\mathrm{O}}(\mathrm{i},\mathrm{t})\) is the GPM (or SMP) precipitation at grid cell \(\mathrm{i}\) and time \(\mathrm{t}\), \(\mathrm{P}_{\mathrm{linear}}(\mathrm{i},\mathrm{t})\) is the corresponding linearly corrected precipitation, and \(\mathrm{a}_{\mathrm{i}}\) for each grid cell \(\mathrm{i}\) is derived on the least square fit between precipitation from CMPA and GPM (or SMP) in the calibration period.
# Towards Client Selection in Satellite Federated Learning
## 3 System Model
### Coverage and Access Time Model
#### 3.2.2 Satellites to Satellites  
As Figure 5 shows, we assume that two satellites can communicate with each other only if the line connecting them is not obstructed by the Earth. Then, we demonstrate how to calculate the visibility between satellites. A space Cartesian coordinate system is established with the Earth's center as the origin, the line connecting the South and North  
Figure 4: Space geometric relationship between the LEO satellite and the GS [25].  
poles as the \(Z\)-axis, and the X-axis pointing to the \(0^{\circ}\) longitude line. We assume that the orbit inclination of satellite \(A\) is \(\theta\) and \(B\) is \(\varphi\), and that the orbit heights are \(h_{A}\) and \(h_{B}\), respectively. At a certain moment, the projection points of satellites \(A\) and \(B\) on the plane where the Earth's equator is located are \(M\) and \(N\), respectively. Then, we set \(\alpha\) and \(\beta\) to express \(\angle MOX\) and \(\angle NOX\). It is worth noting that \(\alpha\) and \(\beta\) are constant because they are orbit inclinations, while the \(\theta\) and \(\varphi\) are parameters that change uniformly over time. Hence, we can obtain the coordinates of these two satellites:  
\[\left\{\begin{array}{c}\overrightarrow{OA}=(h_{A}\cos\alpha\cos\theta,h_{ A}\sin\alpha\cos\theta,h_{A}\sin\theta)\\ \overrightarrow{OB}=(h_{B}\cos\beta\cos\varphi,h_{B}\sin\beta\cos\varphi,h_ {B}\sin\varphi)\end{array}\right. \tag{4}\]  
\[\overrightarrow{AB}=\overrightarrow{OA}-\overrightarrow{OB} \tag{5}\]  
and the minimum distance between origin point \(O\) and line \(AB\) can be expressed by \(OP\), which is perpendicular from point \(O\) to line \(AB\) and can be calculated as follows:  
\[|\overrightarrow{OP}|=\frac{|\overrightarrow{OA}\times\overrightarrow{OB}|}{ |\overrightarrow{AB}|} \tag{6}\]  
Finally, we can determine whether the link is obstructed by the earth based on the comparison of \(OP\) and \(R_{e}\):  
\[\left\{\begin{array}{c}|\overrightarrow{OP}|>R_{e}\quad link\ connected\\ |\overrightarrow{OP}|\leq R_{e}\quad link\ disconnected\end{array}\right. \tag{7}\]