esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 DC Interaction of a Multi-Infeed LCC-HVDC System  
With increasing scenarios of multi-infeed HVDC, vast research has been conducted on the steady-state and transient behavior of AC/DC systems. A few multi-infeed phenomena, such as multi-infeed harmonics analysis, multi-infeed power flow, and multi-infeed direct current interaction, have a lack of literature. However, for a single infeed HVDC system, a direct current interaction with an AC system is discussed in [46]. The analysis is made based on the assumptions of an inverter feeding to a weak AC system, steady-state operation before malfunction, and no voltage control scheme is applied. The converter bus voltage following a variation in DC current undergoes change and obtains another steady-state value. The bus voltage increases to a new steady-state value in response to a step reduction in DC current. The variation in voltage is actually caused by imbalanced reactive power support. An attempt to model multi-infeed direct current interaction is given in [47]. It usesthe mathematical power flow model to derive various indices about multi-infeed HVDC systems. Most importantly, it derives the MIIF using a power flow approach, which is analytically equivalent to a conventional MIIF. The conventional MIIF is based on empirical information, which does not have a rigorous theoretical background. The theoretical framework discussed can help to investigate voltage and power instability. The study also provides basics to probe the insight behavior of voltage and power interaction between converters. The AC side Jacobian matrix is reduced to get the nodal voltage interaction factor, which is equivalent to the MIIF. The incremental reactive power change at only one bus is considered; the reactive power change at other converters' bus is assumed to be zero. This yields two indices, the nodal voltage sensitivity factor and the nodal voltage interaction factor. The nodal DC power and DC current indices are also discussed. The AC/DC power flow Jacobian matrix is reduced with \(\Delta P=0\) and \(\Delta Q=0\); only the change in DC power is assumed. All the converters in a multi-infeed configuration are assumed to be in a constant DC power and constant extinction angle control mode. The nodal current interaction factor is derived as the ratio of change in current at the jth converter to change in current at the ith converter in response of power change at the ith converter.
# Improved Text Summarization of News Articles Using GA-HC and PSO-HC
## 2 Related Work
According to authors of the proposed technique, there is no work existing in scientific literature which addresses the text summarization task with semi-graph approach. The proposed technique uses semi-graph approach ESSg for summarizing text. A meta-heuristic optimization model multi-document text summarization approach is discussed in [30]. The approach uses Cat Swarm Optimization (CSO) algorithm for text summarization of multiple-documents. In [31], authors proposed fuzzy logic for text summarization and cosine similarity function is applied for removing redundancy from the extracted summary. The authors of [32] have discussed a Multi-Modal Summarization (MMS) technique for summarizing text, image, audio, and video. The proposed technique used LexRankalgorithm for audio and text summarization and a cross modal analysis is used to bridge the gap between text and images. In videos key frames are extracted. Semantic analysis is performed using pre trained models on Flickr30K and MSCOCO dataset. **Hybrid Document Summarization (HDS):**  
HDS consists of both single document and multi documents. The authors in [33] introduced a new hierarchical structure based on Recurrent Neural Network (RNN) for extractive text summarization. The model has two levels of attention mechanism applied at word level and at sentence level. A hybrid neural extractive text summarization model known as Contextualized-Representation Hierarchical-Attention Summarization (CRHA-Sum) network is proposed in [34]. The model has ability to learn contextual semantic meaning and features relation for the purpose of text summarization. The model consists of word level attention and sentences level attention. Greedy approach is employed in sentence level attention for selection of sentences. The text summarization model in [35] used clustering and optimization algorithms for text summarization. The model used K-means algorithm for clustering and an extended version of differential algorithm known as binary differential algorithm for text summarization task. The proposed model is known as COSUM. The text summarization model explained by authors in [36] applied sentence role labeling for semantic analysis and an undirected weighted graph model for text summarization. The model summarizes both single document and multiple documents. The model employed PageRank algorithm for generating graphs. The proposed model is called SRL-ESA-TextSum.
## 4 Discussion  
The aerosol contamination research in this paper was based on Sentinel 5p data, which are daily data. However, solutions obtained using other satellites with different spatial and temporal resolutions are available in the literature. In Slovakia, Sentinel 2 data (available every five days) are used to improve local pollution models for high-voltage transmission lines and insulators [54]. Pollution maps of the monthly accumulation of Saharan dust over Israel are conducted using the NASA satellite [55]. On the other side, Sentinel 2 mission data are also used in forest fire area monitoring in sub-Saharan Africa [56]. In contrast to this article, where satellite data were used individually, Sentinel 3 data, combined with Sentinel 2 and Terra MODIS data, can be used to map and track forest fires in burnt areas (e.g., the case study of Nikaragva) [57].  
The FWI adjusted to Croatian conditions presented in this article has already been implemented into the contingency analysis calculation. Landscape monitoring by calculating the NBR and dNBR is also used, as well as an analysis of the possibilities of aerosol contamination monitoring. A significant part of this research was data preparation (Section 2.3.1), from conducting logical data control to cloud removal from satellite data, etc. Despite some missing data and a cloud coverage challenge, it is possible to say that the used data are pretty-high-quality, and in future research it is worth broadly exploring the possibilities of some kind of new cloud mask development for the Sentinel 3 LST dataset.
## 4 Experimental Validation
### Experimental Results
#### 4.3.3 Modal Shear Moduli and Modal Loss Factors  
With the modal frequencies of base beams measured, the shear moduli of base beams can be achieved. With known densities, thickness and modal frequencies, the bending stiffness ratio \(S\) and the geometrical parameter \(Y\) can be determined by Equations (18) and (19), respectively. And then according to Equations (21) and (22), the frequency-dependent dynamic mechanical properties of the VDM can be determined. The modal loss factors and shear moduli obtained by three sandwich specimens are compared and illustrated in Figures 11 and 12, respectively.  
It can be seen from Figures 11 and 12 that the frequency-dependent trend of the measured dynamic mechanical properties of the VDM is obviously concordant, despite that the results are obtained by three distinguished sandwich specimens. This coincidence manifests the effectiveness of the proposed method. Both the shear modulus and loss factor increase with increasing frequency in the range of 50-2500 Hz, which implies that in this frequency range the VDM is in the transition region at the temperature of 26 \({}^{\circ}\)C. Due to the same length and similar bending stiffness, modal frequencies measured by the long asymmetrical and long symmetrical sandwich specimens are similar at the same mode number. It can also be observed that sandwich beam specimens with various compositions and lengths can enrich the tested results, which denotes to estimating modal properties at different frequencies.  
Figure 11: Test results of modal loss factors by three sandwich beam specimens.  
Figure 12: Test results of modal shear moduli by three sandwich beam specimens.
## 4 Results
### Micro-Mechanical Analysis
#### 4.3.3 Micromorphology Analysis  
A microscopic morphological analysis of the 7-day hydration products of single early-strength component polymer mortars was performed by SEM.  
From Figure 6a, it can be seen that the generation of the C-S-H gel from the I-A reference group mortar after 7-day hydration was significantly less than the other groups. Individual fibrous C-S-H gels could be seen almost everywhere and they were not interconnected to form honeycomb C-S-H gels. This is evidence of the decrease in the early-age strength of mortar led by an internal curing agent (ICA). The morphology of the II-B1, the high-absorbent polymeric inner-care mortar with alkanolamine-A incorporated for 7 days, is shown in Figure 6b. It can be seen that a petal-like hydrated calcium sulfoaluminate AFm was formed. This was caused by the water-soluble complexes between the unshared electron pairs of the N atoms on the surface of alkanolamine-A and the metal ions in the cement paste, which sped up the dissolving of C\({}_{3}\)A and C\({}_{4}\)AF and the hydration reaction and improved the early denseness and strength of the cement mortar. From Figure 6c, it can be seen that large amounts of honeycomb C-S-H gel were generated in the II-B2 group, and the generation amount and cross-linking degree were obviously higher than those of the reference group mortar. Adding nitrite could speed up the hydration of the cement and make the mortar more compact. From Figure 6d, it can be seen that the amount of C-S-H gel in the II-B3 group was more than that of the reference group mortar I-A. However, the C-S-H generation was less than that of the polymer mortar group II-B2 with the addition of calcium nitrate. Therefore, it can be concluded that adding alkanolamine-B could have a certain early-age strengthening effect on the high-absorbent polymer mortar, but the effect was not that obvious compared with calcium nitrate.  
Figure 6: SEM electron micrographs of hydration products at 7 days: (**a**) reference group mortar after 7-day hydration; (**b**) mortar with alkanolamine-A incorporated after 7-day hydration; (**c**) mortar with calcium nitrate after 7-day hydration; (**d**) mortar with alkanolamine-B after 7-day hydration.
## 2 Related Works
### Visual Odometry Challenges  
Developing a standalone monocular VO system is a challenging task due to some limitations present in this approach. Using a single camera to track the motion of a robot has two main problems:  
* Scale ambiguity due to the incapacity to perceive the scene depth without any prior information about the environment or an additional source of information.
* Estimation degeneration on pure rotations due to the low overlap between consecutive images.  
In this context, the use of sensors to support VO is important. Inertial sensors are widely used to do so as they can resolve the ambiguities imposed by the monocular scheme [23]. They can be used to refine the estimation of the rotational component [24], to improve the visual estimator performance using short-term motion constraints [25] and/or to be used alongside VO to improve the general motion estimation [26]. Besides this, inertial sensors can also be used to recover the motion scale [27]. However, to perform this task, two main approaches are usually adopted. The first is to use some prior knowledge about the environment, such as the camera height and/or pitch [6; 11], or the size of someknown object present in the camera field of view [28]. The second is the use of range sensors [29; 30; 31], which usually relates the distance measures with the camera perception to recover the depth of a set of pixels.  
Some VO approaches can also be computationally expensive. Many of them use iterative methods that can difficult their use in real-time embedded systems. A solution to speed up these methods is to use heterogeneous computing. There are a few approaches that use GPU-based optimizations to do so. For example, [PERSON] et al. propose a CUDA acceleration for a robot localization and mapping approach [32] where a NVIDIA GPU is considered to run a particle filter. Similarly, [PERSON] et al. [33] propose a VO-optimized approach with GPU-OpenCV optimizations.
# Fuzzy Logic-Based Geographic Routing Protocol for Dynamic Wireless Sensor Networks
## 4 Simulation and Complexity Analysis
### Complexity Analysis  
Judging from the perspective of time complexity, according to the routing process of the FLGR protocol, all the fuzzy sets of the parameters should be traversed once. Assuming there are \(u\) CNs of one EN, and the number of node parameters participating in decision making is \(m\), the time complexity of the comprehensive evaluation fuzzy set obtained is \(o(mu)\). The time complexity of the defuzzification is \(o(u)\). The time complexity of the ranking is \(o(u\log(u))\). Therefore, the total time complexity is \(o(mu)\).
# Analysis of Sentinel-1 Radiometric Stability and Quality for Land Surface Applications
## 4 Conclusions  
The purpose of this study was to assess the radiometric stability and quality of the new SAR sentinel-1A \"S-1A\" sensor. Our results reveal three stable sub-time series with different mean \(\sigma^{\circ}\)-values. The mean \(\sigma^{\circ}\)-values of the first sub-time (between 1 October 2014 and 19 March 2015) series are approximately equal to those of the third (between 25 November 2015 and 1 February 2016) sub-time series (difference lower than 0.3 dB). The \(\sigma^{\circ}\)-values of the second sub-time series (between 19 March 2015 and 25 November 2015) are higher than those of the first and third by roughly 0.9 dB. In addition, our results show that the radiometric stability of the S-1A data of the Ascending and Descending modes is better than 0.48 dB. A comparison with RS-2 data shows that S-1A images acquired prior to 19 March 2015 and after 25 November 2015 appear to be well calibrated with a difference of between S-1A and RS-2 \(\sigma^{\circ}\) (in VV polarization at 32\({}^{\circ}\) and 42\({}^{\circ}\)) lower than 0.3 dB. However, \(\sigma^{\circ}\) S-1A from images acquired between 19 March 2015 and 25 November 2015 are greater than the \(\sigma^{\circ}\) of RS-2 by roughly 1 dB for both 33\({}^{\circ}\) and 43\({}^{\circ}\). This study presents initial results on the radiometric stability and quality of S-1A images acquired prior to February 2016. The use of a longer time series of S-1A images and more reference data are recommended to fully assess S-1A radiometric stability and quality levels.  
The authors wish to thank the National Research Institute of Science and Technology for Environment and Agriculture (Irstea) and the French Space Study Center (CNES, TOSCA 2016) for supporting this work. [PERSON] and [PERSON] conceived and designed the experiments; [PERSON] performed the experiments; [PERSON] and [PERSON] analyzed the results; [PERSON] wrote the paper; [PERSON], [PERSON], and [PERSON] revised the paper.  
The authors declare no conflict of interest.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Invariant Targets**} & \multirow{2}{*}{**Mode (\(\lx@math@degree\)**)**} & \multicolumn{2}{c}{**First Sub-Time Series**} & \multicolumn{2}{c}{**Second Sub-Time Series**} & \multicolumn{2}{c}{**Third Sub-Time Series**} \\ \cline{3-8}  & & **1 October 2014-19 March 2015** & **19 March 2015-25 November 2015** & **25 November 2015-1 February 2016** \\ \cline{3-8}  & & **VH** & **VV** & **VH** & **VV** & **VH** & **VV** \\ \hline \multirow{4}{*}{Racetrack} & A (34.4\({}^{\circ}\)) & - & \(-16.1\pm 0.24(4)\) & - & \(-15.2\pm 0.18(10)\) & - & \(-16.1\pm 0.13(5)\) \\  & D (32.4\({}^{\circ}\)) & - & \(-16.0\pm 0.16(2)\) & - & \(-15.0\pm 0.19(10)\) & - & \(-16.1\pm 0.21(4)\) \\  & A (44.1\({}^{\circ}\)) & - & \(-16.7\pm 0.10(3)\) & - & \(-15.9\pm 0.25(1)\) & - & \(-16.9\pm
## 3 Proposed Method  
Image compression algorithms fundamentally consist of two core processes: encoding, which compresses the image data into a more compact representation, and decoding, which reconstructs the image from the compressed format. Lossless compression algorithms ensure no data loss, making them more precise and reliable than their lossy counterparts. This study presents an enhanced framework for lossless image compression that leverages image segmentation and a novel dynamic bit-level encoding algorithm. The block diagram of the proposed framework is illustrated in Figure 3.  
The original image is first divided into segments using an image segmentation algorithm. At this stage, the most critical factor influencing the success of the compression algorithm is the criterion or parameters used to determine how the image is partitioned. To improve the efficiency of the encoding algorithm and achieve superior compression ratios, a segmentation algorithm that divides the image based on similar colors and textures was employed. To ensure compatibility with lossless compression, a specialized file format was developed for storing the segmented images. This format is critical for accurately reconstructing the original image.  
The framework is detailed under three main sections: (a) Image Segmentation, (b) Packaging Technique for Image Segments, and (c) DEA.
## 1 Introduction
[3] studied the mechanism of cleaning efficiency enhancement, they found liquid water is in the irradiation process, where ionized free electrons cannot escape, and a large number of ions or nuclei constantly collide to produce a sufficient sizeable kinetic energy, so that the cleaning efficiency is improved. In summary, the selection of laser processing medium is still mainly concentrated in the liquid; the water layer has a good cleaning effect, but there needs to be more relevant results of in-depth study. In addition, SiO\({}_{2}\) possesses a high melting point, which enables it to maintain its stability. When utilized in mechanical processing for the removal of surface films, it exhibits good efficacy [19]. Moreover, when in a colloidal state, its removal efficiency is significantly enhanced [20]. Based on the aforementioned research, SiO\({}_{2}\) is utilized as an auxiliary medium in laser cleaning to investigate its influence on the cleaning efficiency. Research within the realm of assisted laser cleaning is currently somewhat constrained, with the primary focus being on the fine-tuning of parameters that affect surface morphology during the cleaning procedure and the examination of how different cleaning media impact efficiency. However, there is a notable gap in the understanding of the fundamental cleaning mechanisms and principles when lasers interact with various media, as well as the challenges posed by limitations within individual media. To address this, the present study delves into the intricacies of continuous laser cleaning across a spectrum of media settings. The objective is to elucidate the outcomes of laser cleaning when enhanced by liquid, solid, and solid-liquid mixtures on aspects such as surface morphology, cleaning depth, and surface roughness. The research also endeavors to enhance the efficacy of continuous laser cleaning techniques. Furthermore, this paper synthesizes the variations in cleaning dynamics for rust layers in diverse media contexts, with the goal of offering theoretical guidance for the advancement of laser cleaning technologies.
# Challenges Associated with Implementing 5G in Manufacturing
## 1 Introduction
### Enhanced Mobile Broadband (eMBB)  
eMBB can initially be addressed by the expansion to existing 4G services as it aims to service more densely populated metropolitan centers with downlink speeds approaching 1 Gbps (gigabits-per-second) indoors, and 300 Mbps (megabits-per-second) outdoors. One way to accomplish this is through the installation of extremely high-frequency millimeter-wave (mm-Wave) antennas. For areas that are more urban outlying and beyond into rural setting areas, eMBB will work towards replacing 4G's current LTE (Long-Term Evolution) scheme, with a new network of lower-power omnidirectional antennas providing 50 Mbps downlink service. eMBB traffic can be deemed to be an addition to the 4G broadband service currently available. It is capable of large payloads and a by-a-device activation pattern that is capable of remaining stable over an extended time interval. This allows the network to schedule wireless resources to the eMBB enabled devices such that no two eMBB devices compete or access the same resource simultaneously [3]. To provide these, it is expected that 5G will deliver:  
* Traffic capacity of up to 10 Mbps per sq. metre in hotspot areas.
* Data transfer rates the user experiences of up to 1 Gbps with peak data rates of transfer in the tens of Gbps and a capacity of maximum traffic volume of at least 1 Tbps per sq. kilomet.
* Latency as low as 1 ms for user experience levels of data exchange.
* Connection density of up to one million connections per sq. kilomet.
* High mobility, facilitating connectivity up to 500 km/h in high-speed trains and up to 1000 km/h in aeroplanes, with enhanced user experience.  
Figure 1: 5G key usage scenarios.
# Micro-Raman Spectroscopy Investigation of Crystalline Phases in EAF Slag
## 3 Results and Discussion
### Raman Spectroscopy  
The three areas of sample A analysed by SEM-EDXS and 2D XRD were tested by using \(\mu\)-Raman analysis (about 2 microns spots) and the spectra of each crystalline phase were identified [19].  
The Raman spectra of the grain identified as larnite are reported in Figure 3a, and they are in good agreement with the Raman spectra reported in the literature [20]. The most significant Raman features of this phase are the bands at about 848, 860 and 977 cm\({}^{-1}\). Larnite can exist in different structures (namely, \(\gamma\)-phase and \(\beta\)-phase), and this Raman spectrum corresponds to the \(\beta\)-larnite phase. A large band of about 700 cm\({}^{-1}\) is also present in the spectra. Since Fe was always detected in the larnite grains by EDXS (Table 3), the band can be attributed to iron oxide impurities. Indeed, brownmillerite and magnesioferrite, as well as magnetite, have strong bands at about 700 cm\({}^{-1}\)[21].  
Figure 1: SEM micrographs of sample A performed in three different areas. EDXS measurements were collected in the squares.  
Figure 2: XRD patterns of three different (\(300\times 300\)\(\mu\)m\({}^{2}\)) areas of sample A and the main crystalline identified phases.  
In the second area (see Figure 3b), the presence of magnesioferrite phase is confirmed by the band at about 750 cm\({}^{-1}\), due to the stretching A\({}_{1g}\) mode, and the T\({}_{2g}\) bands at about 500 cm\({}^{-1}\) and 600 cm\({}^{-1}\)[22]. In this spectrum, the main band of larnite at 860 cm\({}^{-1}\) is also detected, as well as other minor signals that can be attributed to disordered iron oxides [19; 21; 23; 24].  
In Figure 3c, the spectrum to that of the brownmillerite. The brownmillerite phase can present containing Al and Fe (Ca\({}_{2}\)(Al,Fe\({}^{3+}\))\({}_{2}\)O\({}_{5}\) and the Al content affects the position of the main Raman band, which shifts to the right (from about 710 to 750 cm\({}^{-1}\)) [25]. In our sample, brownmillerite is identified from the band at around 740 cm\({}^{-1}\), suggesting a significant Al content [26; 27; 28]. A band at about 300 cm\({}^{-1}\), characteristic of the brownmillerite phase, is also present [29]. Other bands are likely due to the presence of minor phases.  
In samples B, C, D and E, XRD on powder makes it possible to identify further crystalline phases like gehlenite, wustite e magnesiochromite (see Figure 4). By \(\mu\)-Raman analysis, the spectra of each phase were identified to be in good agreement with the literature [30; 31; 32; 33]. All the collected Raman spectra are reported in the Supplementary Material.  
Figure 3: (**a–c**) \(\mu\)-Raman images (50\(\times\) objective) and spectra of identified phases in the three areas of sample A.