esa-sceva/satcom-chunk-collection huggingface dataset:
# Enhanced Tone Mapping Using Regional Fused GAN Training with a Gamma-Shift Dataset
## 3 Proposed Model
### Gamma Shift Dataset for Tone Compression Generative Adversarial Network Training  
This section describes how the gamma shift was applied to training datasets. Training HDR images requires various EVs. The gamma shift dataset is proposed to train a wide range of brightness information. In the conventional CycleGAN model, all color channels are used for training input, and the generator causes color distortion. However, unnecessary color information need not be trained. Training only the luminance space reduces the training time and avoids the color distortion problem. When the module was trained, only the luminance channel \(L\) was used, whereas _ab_ color channels were maintained.  
Gamma values of 1.2, 1.4, and 1.6 were used with similar brightness levels for the low-level dataset. Figure 2 is an example of a dataset used for training. Figure 2a-c show the target data, EV dataset, and gamma shift dataset, respectively. It is assumed that the partial brightness values of the improvement images to be learned are random. However, Figure 2b is increasingly dimly composed of EV-3, EV-4, and EV-5. Nonetheless, although there were bright areas, the amount of learning in these areas was expected. Figure 2c, on the other hand, is a dataset of the proposed model that has varying degrees of exposure in bright and dark areas, providing an advantageous environment for training networks to learn various brightness ranges.Its will be the appearance of over saturation in some parts of the image when learning bright areas by increasing the EV. Information is lost in the over saturated region. It causes color distortion in the image generated by CycleGAN.  
That is to say that it has limitations in learning a wide range of luminance channels. Figure 3a shows that EV shift image information was irrecoverable in high-level luminance. When dark images are inputted, GANs attempt the output bright images due to their nature of attempting to create target images. Inputting a bright image into such a trained module saturates the bright area in the resulting image. As shown in Figure 3a, the EV is generated similarly to the expected image for low-level regions, but the resulting value does not match the expected image for high-level regions, with it instead losing information. Meanwhile, the proposed model learns a wide range of brightness exposure information with no information loss, which is appropriate for training on luminance maps and beneficial for training the local tone of images to approximate the expected image (Figure 3b). Therefore, training image tone compression over a wide luminance range with the gamma shift dataset was necessary.  
Figure 2: Data organization for the experiment: (**a**) source data, (**b**) exposure value (EV) data [18], and (**c**) gamma shift data.
## 3 Results
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{3}{c}{**DSC (\%)**} & \multirow{2}{*}{**MHD (mm)**} \\ \hline  & **Measurement 1** & **Measurement 2** & **Measurement 3** & \\ \hline Conventional U-net & 86.44 \(\pm\) 2.24 & 44.16 \(\pm\) 4.18 & 67.51 \(\pm\) 3.59 & 0.89 \(\pm\) 0.14 \\ U-net + BSU-pooling layer & 87.30 \(\pm\) 3.16 & 50.68 \(\pm\) 5.50 & 71.68 \(\pm\) 4.76 & 0.88 \(\pm\) 0.14 \\ U-net + BSU-layer & 87.19 \(\pm\) 2.67 & 51.88 \(\pm\) 5.67 & 71.68 \(\pm\) 5.48 & 0.90 \(\pm\) 0.18 \\ Cascaded U-net & 87.70 \(\pm\) 4.00 & 50.25 \(\pm\) 8.68 & 71.33 \(\pm\) 7.63 & 0.86 \(\pm\) 0.17 \\ BSU-net & 89.44 \(\pm\) 2.14 & 54.62 \(\pm\) 4.59 & 74.85 \(\pm\) 3.20 & 0.81 \(\pm\) 0.10 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: DSC and MHD measurements for five different networks including conventional U-net, BSU-net and three different networks applying several components of BSU-net. Figure 6: Segmentation result from networks. Brown area, yellow area, and blue area denote correctly segmented area, under-segmented area, and over segmented area, respectively. (**a**) Input image. (**b**) U-net result. (**c**) Dilated U-net result. (**d**) BSU-net result.
## 3 Amphiphilic Miktoarm Star Polymers: Self-Assembly
### Micelle Characteristics: CMC and Stability
It has been well documented for miktoarm star polymers, especially those containing PCL, in varied systems, including ABC (PEG-PCL-TPPBr) (triphenylphosphonium bromide) and PEG-PCL-PAA, as well as more complex A(AB)\({}_{3}\), A\({}_{2}\)(AB)\({}_{2}\), and A\({}_{3}\)(AB) (A = PEG, B = PCL) systems [56, 42, 57]. One interesting example was of an AB\({}_{2}\) (A = PEG, B = P(MAA-co-MMA) miktoarm star, where poly(methacrylic acid) (PMAA) was a pH-responsive unit. Polymers containing higher hydrophobic PMMA to hydrophilic PMAA content ratios led to more compact and stable micelles and lower CMCs, with the trade-off that they were comparatively less pH-responsive [62]. While hydrophobicity tends to decrease CMCs, they generally increase with increasing hydrophilic block sizes [56, 72]. Rather than strictly increasing hydrophobic block sizes, one study attempted to change the ratio of hydrophilic and hydrophobic segments through four different A\({}_{2}\)B, A\({}_{2}\)B\({}_{2}\), AB\({}_{3}\), and A\({}_{3}\)B (A = PCL, B = POEGMA) miktoarm star polymers [70]. It was found that increasing the number of PCL arms to POEGMA resulted in the largest increase in micelle stability, with a minimum CMC of 2.66 mg/L for the A\({}_{3}\)B miktoarm star. Interestingly, despite PCL/POEGMA ratios, the 4-armed miktoarm stars collectively had lower CMCs than the 3-armed A\({}_{2}\)B miktoarm star. This reciprocated an earlier study where more arms in star polymers increased micelle stability [132]. Similarly, the 3-armed star had the highest diameter of 73 nm, and the size decreased with the number of PCL arms in 4-armed miktoarm star polymers to 28 nm.
# Graphene-Based Flexible Electrode for Electrocardiogram Signal Monitoring
## 2 Research on Graphene-Based Flexible ECG Electrodes
### Modified-Graphene-Based ECG Electrodes
#### 2.5.2 Environmentally Friendly Chemically-Modified Graphene ECG Electrode  
Chemical reduction of GO using biocompatible materials is an environmentally friendly way to produce graphene electrodes. [PERSON] et al. used glucose as the reducing agent to fabricate biocompatible, glucose-treated, chemically modified graphene (GCG) through a solvothermal technique (180 \({}^{\circ}\)C, 2 h in a convection autoclive) [69]. After acidic treatment (1 M acetic acid, 5 h), the GCG was transferred to a contamination-free CG suspension. Then, through filtration, the GC film was cast onto a nylon filter paper to create an ECG electrode (Figure 4b). The achieved graphene electrode can detect the characteristic peaks of the ECG signal. Besides, it provides an environmentally friendly method for producing graphene ECG electrodes.
# Fully Open-Source Meeting Minutes Generation Tool
###### Abstract  
With the increasing use of online meetings, there is a growing need for efficient tools that can automatically generate meeting minutes from recorded sessions. Current solutions often rely on proprietary systems, limiting adaptability and flexibility. This paper investigates whether various open-source models and methods such as _audio-to-text_ conversion, _summarization_, _keyword extraction_, and _optical character recognition (OCR)_ can be integrated to create a meeting minutes generation tool for recorded video presentations. For this purpose, a series of evaluations are conducted to identify suitable models. Then, the models are integrated into a system that is modular yet accurate. The utilization of an open-source approach ensures that the tool remains accessible and adaptable to the latest innovations, thereby ensuring continuous improvement over time. Furthermore, this approach also benefits organizations and individuals by providing a cost-effective and flexible alternative. This work contributes to creating a modular and easily extensible open-source framework that integrates several advanced technologies and future new models into a cohesive system. The system was evaluated on ten videos created under controlled conditions, which may not fully represent typical online presentation recordings. It showed strong performance in audio-to-text conversion with a low word-error rate. Summarization and keyword extraction were functional but showed room for improvement in terms of precision and relevance, as gathered from the users' feedback. These results confirm the system's effectiveness and efficiency in generating usable meeting minutes from recorded presentation videos, with room for improvement in future works.  
meeting minutes generation; presentation video; audio-to-text; summarization; keyword extraction; OCR; SSIM; _Whisper_ model; BART LM +
Footnote †: journal:  
Article  
Fully Open-Source Meeting Minutes Generation Tool
# Development of Enabling Technologies for Ku-Band Airborne SATCOM Phased-Arrays
## 3 Antenna Design
As expected, the degradation of the performance at lower pointing angles is due to the different orientation angles of the tiles, which are involved in the beam forming, with respect to the horizon. Figure 3: G/T vs. elevation angle over the horizon (**a**) and typical azimuth Rx radiation pattern (**b**). Figure 2: Faceted hemi-spherical antenna. The typical azimuth receiver antenna pattern is shown in Figure 3b. During the transmission, all the active devices are able to work at the maximum power level and the expected performance in term of EIRP are reported Figure 4: The minimum guaranteed value is in the order of 43 dBW over the complete antenna field of view. The antenna is also able to control the transmit antenna patterns side-lobe in order to respect the applicable regulatory recommendations such as ETSI in the European countries [7] and the FCC in the United States. The typical azimuth transmit antenna pattern is reported in Figure 5a. The black line represents the mask that has been imposed in the optimization process (corresponding to the ETSI mask for 512 KHz bandwidth). The corresponding elevation transmit antenna pattern is shown in Figure 5b.
## 2 System Structure and Working Principle
### Converter  
Converters are a vital part of a PV-ESS system. Inverters are a key factor affecting the economics of PV-ESS systems. From the perspective of the users of PV systems, the economy, high efficiency, reliability, and service life are the main requirements for inverters. As the output of PV has strong randomness and instability, it is necessary to add bidirectional DC/DC converters between the PV panels and the ESS to control the stability of the charging and discharging processes of the ESS and ensure the reliability of the system. Therefore, DC/DC converters are required to have higher power density and efficiency, and their control mode and structure should be relatively simple to improve the stability and service life of the system. Given the above, the parameters of each component are shown in Table 2.
# Remote Sensing of Snow Cover Using Spaceborne SAR: A Review
## 5 Discussion
### Opportunities of Data Fusion for SAR-Based Snow Cover Detection
#### 5.6.2 SAR Polarization (co- and Cross-Polarization)  
Several studies indicated that the influence of LIA on the backscattering difference between dry and wet snow is also polarization-related, and that cross-polarization can preserve a better difference under small LIA conditions [140; 219]. Hence, the combination of different polarizations could be a promising option. [PERSON] et al. [140] calculated the ratio map for VV and VH independently and fused them with their weights based on LIA. So far, however, no other study investigated this potential and, therefore, more research is required.
# Recent Progress Trend on Abrasive Waterjet Cutting of Metallic Materials: A Review
## 5 Conclusions and Potential Future Scope of Study
### Conclusions  
* The intensive review of the trend of recently published research studies has revealed that aluminium and other metal workpieces gained 53% of the attention in exploring AWJM application improvements. A total of 27% of recent studies have proved that traverse speed greatly impacts abrasive waterjet (AWJ) cutting performance, followed by abrasive mass flow rate and waterjet pressure with statistics of 22% and 20%, respectively. Garnet with a hardness scale of MOHS 7-8 and a mesh size of #80 at 180 \(\upmu\)m gained 90% utilisation in AWJM applications due to its better performance and competitive price.
* AWJ cutting of hard-to-cut workpieces such as metallic materials including tungsten carbide, tool steel, and Inconel alloys have demonstrated distinct characteristics such as the fast speed at a rate of 2 to 3 mm\({}^{3}\)/s, versatility in cutting with thickness ranging from \(\leq\)304.8 mm, the ability to machine complicated shapes, and environmentally sustainable qualities. These characteristics explain their wide range of current applications across various industries.
* Cutting metallic materials with low machinability, i.e., stainless steel, Inconel and titanium, can attain lower surface roughness, higher depth of cut and material removal rate at a waterjet pressure ranging from 201 to 300 MPa. A traverse speed ranging from 60 to 90 mm/min, abrasive mass flow rate of 401 to 500 g/min, and stand-off distance ranging from 1.0 to 3.0 mm were established to achieve a lower surface roughness, lower kerf taper angle, and higher material removal rate applicable to various metals. Different optimisation techniques such as weighted principal components analysis (WPCA), surface and Box-Behnken methodology (RSM-BBD) and grey wolf optimiser (GWO) were employed and proved to be notably efficient in defining the optimum values of process parameters.
# Super-Resolution Remote Imaging Using Time Encoded Remote Apertures
## 3 Reconstruction Algorithm
### Adding a Vertex  
After core is found, next step is to iteratively add a vertex to the core. First, we choose a random tetrahedron from the current structure. The next step is to search over all possible combinations of four distances from the remaining distance pool. Three distances will form one first and two second bounce distances. The remaining distance is used to test the bridge bond for the chosen rigid substructure. For instance, in Figure 2d \((p_{0},p_{1},p_{2},p_{3})\) is chosen as a rigid substructure and \(p_{4}\) is added point while using one first bounce \([p_{0},p_{4},p_{0}]\) and two second bounces (\([p_{0},p_{1},p_{4},p_{0}]\) and \([p_{0},p_{2},p_{4},p_{0}]\)). The second bounce \([p_{0},p_{3},p_{4}]\) is used for the bridge bond check.  
```
input : Distance list \(\beta\) output : Reconstructed point-cloud CoreFinding() whileCore is not founddo  Choose D=3 entries(random) from the distance list \(\beta\), and test all possible two first and one second bounce pairs to construct base triangle ifa base triangle is foundthen  Choose D=6 entries from the distance list \(\beta\), and test all possible two first and four second bounce pairs to construct two tetrahedra with the base triangle iftwo tetrahedra are foundthen  choose D=1 entry from the distance list \(\beta\), and do bridge bond test. ifb bridge bond test is passedthen  Core is found  end if  end if  end if  AddVertex() whileDistance list \(\beta\) is not emptydo  Choose(random) four points(tetrahedra) from the substructure including the origin point  Choose D=3 entries from the distance list \(\beta\), and test all possible one first and two second bounce pairs in order to construct tetrahedra with one side lying on the previously chosen tetrahedra iftetrahedra is foundthen  Choose D=1 entry from the distance list \(\beta\), and apply bridge bond test. ifb bridge bond test is satisfiedthen  Add tetrahedra to the existing substructure and remove used entries from \(\beta\)  end if  end if  end return point-cloud;
```  
**Algorithm 1**Modified TRIBOND
## 2 System Description
### Structrue of PV/T Panel  
The PV/T panel in this study is a sheet-and-tube PV/T solar collector. As shown in Figure 3, the PV/T panel consists of glass cover, mono-crystalline silicon cells, aluminum absorber plate, copper tubes, and insulation layer. The PV cells are packaged and attached to the absorber plate with a packing factor of 0.85. The air gap between the glass cover and the PV cells can help to reduce the heat loss from the upper surface. Direct flow absorber is adopted to reduce the water flow resistance in the tubes. Six parallel copper tubes (i.e., collector risers) with a diameter of 8 mm are welded at the bottom of the absorber plate. Both ends of the copper tubes are welded with two headers with a diameter of 22 mm. The PV cell efficiency at reference conditions (at irradiation intensity of 1000 W/m\({}^{2}\) and temperature of 25 \({}^{\circ}\)C) is 15%.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Latitude and Longitude of Guangzhou** & **23\({}^{\circ}\)08\({}^{\prime}\) N, 113\({}^{\circ}\)20\({}^{\prime}\) E** \\ \hline Window height (mm) & 1800 \\ Window width (mm) & 1600 \\ Embedded depth of windowpane (mm) & 200 \\ Tilt angle of panel (\({}^{\circ}\)) & 28 \\ Panel width (mm) & 646 \\ Panel length (mm) & 2648 \\ Gross area of panel (m\({}^{2}\)) & 1.71 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Parameters of the window and PV/T panel.  
Figure 2: Schematic of a PV/T panel used as horizontal sunshade.
# Sugarcane Yield Mapping Using High-Resolution Imagery Data and Machine Learning Technique
## 2 Materials and Methods
### Imagery Data  
Fifty-four orbital images from Sentinel-2 were used by considering 2018/2019 and 2019/2020 sugarcane growing seasons. This satellite constellation uses a multi-spectral instrument with 13 spectral channels with a 290-km swath width. All images were downloaded from the United States Geological Survey (USGS) via the Earth Explorer (earthexplorer.usgs.gov). These images were selected with low cloud cover (<1%) and clipped to the region of interest. All images were projected on the WGS/UTM zone 22S. An internal buffer of 5 m was applied to each field boundary using a Quantum Geographic Information System (QGIS 2.18.26) [34] to ensure that the spectral data corresponded to the sugarcane plants. The original orbital images were submitted to atmospheric correction before each VI calculation using a free open source plugin Semi-Automatic Classification  
Figure 1: Location of sugarcane fields study site in Brazil. 5.4.2 [35] on QGIS 2.18.26 [34]. This was done to convert the digital numbers to reflectance data, considering the DOS1 (Dark Object Subtraction) atmospheric correction methodology [36]. Five spectral bands from Sentinel-2 were considered in this study (Table 1). The most common VIs cited in the literature for crop yield monitoring were calculated. Four VIs were evaluated (Table 2) throughout the sugarcane development cycle, which included the NDVI [37], Normalized Difference Red-Edge Index (NDRE) [38], GNDVI [39], and Wide Dynamic Range Vegetation Index (WDRVI) [40]. As suggested by [PERSON] et al. [41] and [PERSON] et al. [42], the value 0.1 was adopted for the weighting coefficient (a) of WDRVI. Table 3 summarizes the dates of orbital images taken and the respective phenological stage of sugarcane according to [PERSON] and [PERSON] [43]. Each phenological stage was identified according to the DAC to standardize the variables for data processing of both seasons. No images for the initial growing stage were found without cloud cover. All images with low cloud cover (<1%) collected during the sugarcane development cycle were considered for evaluating the potential of free orbital images to assess crop yield. \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Spectral Bands**} & \multirow{2}{*}{**Central Wavelength (nm)**} & \multicolumn{3}{c}{**Resolution**} \\ \cline{3-5}  & & **Spatial (m)** & **Temporal (Days)** & **Radiometric (Bits)** \\ \hline B2 Blue & 490 & & & \\ B3 Green & 560 & & & \\ B4 Red & 665 & & & \\ B8 NIR & 842 & & & \\ \hline B5 Red-Edge & 705 & 20 & & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Specifications of the spectral bands from Sentinel-2.
## 4 Traffic Filtering-Based Techniques  
Traffic filtering-based techniques reduce the redundant traffic by solving some or all the issues related to HSR mentioned in Section 3. There are several traffic filtering-based techniques, as follows:  
* Quick removing (QR): QR removes duplicated and circulated traffic from rings.
* Traffic control (TC): TC also removes duplicated and circulated traffic from rings, like QR.
* Port locking (PL): PL prunes unicast traffic for DANH rings.
* Enhanced port locking (EPL): EPL is an enhanced version of the PL approach. The EPL approach prunes unicast traffic for both DANH and QuadBox rings.
* Filtering HSR traffic (FHT): FHT filters unicast traffic for both DANH and QuadBox rings and removes duplicated and circulated traffic in the rings.  
Table 1 summarizes traffic filtering features of these techniques.
## 4 WiFi 6/6E: IEEE 802.11 ax
### Higher-Order Modulation Schemes  
The WiFi 6 standard supports 1024 quadrature amplitude modulation (QAM) with a 5/6 coding rate. With this modulation scheme, 1.2 Gbps of data rate per spatial stream can be achieved. Hence, WiFi 6 is capable of providing Gbps data rates without MIMO if the channel conditions are favourable. In addition, with multiple spatial streams, it is possible to reach beyond 10 Gbps. As a result of incorporating 1024-QAM in WiFi 6, a 25% improvement in throughput is achieved in comparison to 802.11 ac [39].
## 4 Discussion
### Limitations and Perspectives  
This study also has certain limitations and uncertainties. Firstly, our cropland use data is obtained from remote sensing monitoring. Inherent scale effects and mixed pixel issues in remote sensing pixels may introduce uncertainties in identifying fragmented cropland in mountainous and hilly areas of Guangdong Province, potentially leading to an underestimation of calculated results, which is difficult to avoid completely. Secondly, for a more refined framework of grain production estimation, we did not consider the impact of non-grain on food production. In some areas, non-grain cultivation is severe, up to 50% [58]. However, non-grain is generally considered an adjustment of cropland planting structure and thus not classified as a type of cropland use transition. Finally, we did not account for yield differences caused by the conversion between paddy fields and drylands. Typically, paddy fields have higher productivity than drylands. Future research should incorporate the impact of non-grain into the food production estimation framework and refine yield differences between paddy fields and drylands.