esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Methods  
SBAS\(-\)InSAR [41] and PS\(-\)InSAR [42] have become the most commonly used technologies for obtaining deformation time-series data and have achieved very good results in the monitoring of many landslides. Therefore, this paper combines SBAS\(-\)InSAR and IPTA [43] technology developed based on PS\(-\)InSAR and leverages the advantages of the free combination of interference pairs in SBAS and the iterative characteristics of IPTA to obtain continuous, high-precision deformation data. Then, the results are superimposed on DEM and optical images for landslide detection. In this paper, SRTM DEM with a resolution of 30 m is used as DEM data and Google Earth images with an approximate resolution of 0.5 m are used for optical data. The DEM data are used to determine the slope of the terrain; usually, areas with a slope of less than 10\({}^{\circ}\) are considered free of landslides. During the InSAR monitoring period, only some areas of slopes will undergo obvious deformation. It is thus difficult to fully characterize the entire landslide only from the InSAR deformation results. Hence, it is necessary to utilize the auxiliary optical images for better detection [44,45]. Based on the high-precision landslide-identification/monitoring system, this paper uses Sentinel\(-\)1A and ALOS/PALSAR\(-\)2 as data sources to detect landslides and compares the differences between the two data types in terms of deformation rate and recognition. Further, this investigation explores the reasons for the differences between the two data sources by calculating the visibility, the coherence of the interference pairs, the quality of unwrapped images, and the rate and time-series results for single landslide points. Finally, the overall adaptability of the two data types and suggestions for future landslide-detection methods are summarized. The specific technical process of landslide detection and analysis is shown in Figure 3.  
Figure 2: Temporal and spatial baseline diagrams. (**a**) Sentinel\(-\)1A, (**b**) PALSAR\(-\)2. The blue circle represents the temporal position and spatial relative position of the image.  
Figure 3: Flowchart for the detection of potential landslides in the Qinling-Daba Mountains.
# Toward SDM-Based Submarine Optical Networks: A Review of Their Evolution and Upcoming Trends
## 6 Submarine Power Feeding
Moreover, there exists an optimal combination of the number of pump amplifiers and the power from their FPs that results in maximum EOPCE. The derived model enables the analysis of the cable systems' efficiency by calculating the total capacity achieved for a given amount of electrical power. [PERSON], [PERSON] et al. in [74] studied power efficiency of SDM-based submarine systems calculated from a total system's capacity per unit of power consumption. The authors reported on numerous experiments considering various values of system power and length spans. They comment on potential performance gains that may occur by optimizing the cable system design and they estimated the optimal number of FPs and the system's total capacity for specific submarine system's length span. Finally, Figure 32 demonstrates a comparison concerning power feeding versus system capacity for two cable system links, one transpacific (10,000 km) and one transatlantic (6000 km). In this scenario, the power-feeding values vary from 15 kV (for legacy systems) to 18 kV (for the latest-generation systems) compared to system capacity, increasing from 16 to 32 FPs. The results show that a 20% improvement of power output translates into an over 50% increase in system capacity by increasing the fiber pairs in a long-haul transoceanic system, lowering the cost per Tb/s. Another important aspect is the enhanced reliability resulting from the extension of single-end system power-feeding distance which is a crucial parameter under fault conditions or during system-maintenance operations.
## 2 Related Works
Additionally, different designs of DT, such as Fine Tree (FT), Medium Tree (MT), and Coarse Tree (CT), are also thoroughly analyzed. In [31], the author has applied SVM as the classifier and 4 th-order cyclic cumulant feature to classify three modulation types such as ASK, BPSK, and QPSK by assuming that the channel noise is in the range of \(-10\sim 10\) dB. The experiment result shows that the 4 th-order cyclic cumulant feature has an efficient discrimination capability in both non-noisy and noisy channels [31].
# Scaling of FAPAR from the Field to the Satellite
###### Abstract  
The fraction of absorbed photosynthetically active radiation (FAPAR) is a critical biophysical parameter in eco-environmental studies. Scaling of FAPAR from the field observation to the satellite pixel is essential for validating remote sensing FAPAR product and for further modeling applications. However, compared to spatial mismatches, few studies have considered temporal mismatches between _in-situ_ and satellite observations in the scaling. This paper proposed a general methodology for scaling FAPAR from the field to the satellite pixel considering the temporal variation. Firstly, a temporal normalization method was proposed to normalize the _in-situ_ data measured at different times to the time of satellite overpass. The method was derived from the integration of an atmospheric radiative transfer model (6S) and a FAPAR analytical model (FAPAR-P), which can characterize the diurnal variations of FAPAR comprehensively. Secondly, the logistic model, which derives smooth and consistent temporal profile for vegetation growth, was used to interpolate the _in-situ_ data to match the dates of satellite acquisitions. Thirdly, fine-resolution FAPAR products at different dates were estimated from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data using the temporally corrected _in-situ_ data. Finally, fine-resolution FAPAR were taken as reference datasets and aggregated to coarse resolution, which were further compared to the Moderate Resolution Imaging Spectroradiometer (MODIS) FAPAR product. The methodology is validated for scaling FAPAR from the field to the satellite pixel temporally and spatially. The MODIS FAPAR manifested a good consistency with the aggregated FAPAR with \(R^{2}\) of 0.922 and the root mean squared error of 0.054.  
f  
f raction of absorbed photosynthetically active radiation; scaling; validation; MODIS; _in-situ_ data; coarse resolution
## 3 Results  
### Wheat Aphids Occurrence  
Based on the investigated data, the results show that, both the cropping pattern (\(\chi^{2}\)=183.47, \(df=1\), \(p<\) 0.001), and the year (\(\chi^{2}\) = 70.53, \(df=2\), \(p<\) 0.001) have a significant influence on the number of wheat aphids. Meanwhile, the interactions between cropping method and year are also significant with (\(\chi^{2}\) = 167.11, \(df=2\), \(p<\) 0.001).  
The results of the year-wise study on the link between the wheat aphids and cropping modes indicate that the number of wheat aphids while practicing a walnut-wheat intercropping system is higher than that recorded via a monocropping system of wheat production: the year 2017 (\(z\) = 2.38, \(p\) = 0.02), the year 2018 (\(z\) = 10.01, \(p<\) 0.001), the year 2019 (\(z\) = 18.19, \(p<\) 0.001) (Figure 1). Further results demonstrate that the walnut-wheat intercropping system records a lower number of wheat aphids in 2017 than the number tabled in 2018 (\(z=-10.30\), \(p<\) 0.001) and in 2019 (\(z=-6.85\), \(p<\) 0.001). Concurrently, the mean number of wheat aphids in 2019 is significantly lower than 2018 (\(z=-3.38\), \(p=\) 0.002).  
Contrary to the results of this study regarding the linkage between the wheat aphids and the cropping systems as discussed in the preceding paragraph, the figures for such a link are different in the wheat monocropping system. For example, the number of wheat aphids in 2019 is significantly lower than the number in 2017 (\(z=-11.73\), \(p<\) 0.001) and 2018 (\(z=-10.41\), \(p<\) 0.001). However, there is a slight statistical difference in this number between the years 2017 and 2018.
## 3 Results and Discussion
### Mechanism Analysis
As shown in Figure 8, 4-\(\mu\)L water droplets were quickly absorbed into the cavity of the copper foam skeleton within 16 ms for all samples. This result is obtained because the strong liquid absorption performance of copper foam is mainly due to its micrometer-size cavities and high porosity. Thus, we cannot clearly observe the apparent contact angle between water droplets and the surface of copper foam. Figure 7: Picture of solidification progress of Blank and CF#300s. However, on the basis of Equations (4)-(9), we can calculate the heterogeneous ice nucleation rate at different supercooling and roughness, which is shown in Figure 9. The inset shows the intrinsic contact angle of a smooth copper surface, which is approximately 82.5\({}^{\circ}\). This value is consistent with those in other studies [28; 31; 32; 33]. Figure 9 shows that at the same supercooling, the nucleation rate increases as the roughness factor \(f\) increases. This result demonstrates that at the same nucleation rate, the surface with a larger surface roughness factor \(f\) has smaller supercooling. As shown in Figure 6, the sample with a longer deposition time has larger surface roughness; thus, it has a larger nucleation rate at the same supercooling, i.e., it requires smaller supercooling to obtain the same nucleation rate. Figure 8: Wettability measurement for different samples using a 4-\(\mu\)L water droplet. Figure 6:0 Heterogeneous nucleation rate under different supercooling and surface roughness (the inset shows the intrinsic contact angle of a smooth copper surface).
## 3 Results
### Case 2: Results Using Rural SAR Data and Pre-Computed FRP Maps
This shows the correspondence between the modelled  
Figure 12: **(a)** Correspondence between the Flood Foresight model flood extent (combined with that of the SAR in urban areas) and aerial photo flood extent, in urban and rural areas of Tewkesbury, superimposed on the LiDAR image of the urban area (lighter grey – higher), and (**b**) correspondence between the Flood Foresight model flood extent and aerial photo flood extent in the long 6 km rural reach of the Severn immediately north-west of Tewkesbury (Mythe Bridge in the south of (**b**) is visible in the north-west of (**a**)). flood extent and the aerial photo flood extent in the long 6 km rural reach of the Severn immediately north-west of Tewkesbury. Over this reach, the hit rate was 96%, the precision 88%, and the CSI 85%. Figure 12a also shows that Flood Foresight predicted flooding well in the smaller rural areas immediately surrounding the urban area. In dynamic situations such as the above, it is likely to be advantageous to use assimilation to combine the SAR and model WLO maps and assimilate a sequence of SAR WLO maps into the model WLO maps as they evolve over time, in order to improve the latter. As discussed previously, this would require overcoming the difficulty of updating the model WLO maps with height innovations, because of the simulation library approach used in the modelling.
# MEC: A Mesoscale Events Classifier for Oceanographic Imagery
## 3 Types of Patterns  
As mentioned in the Introduction, the geomorphological features in the ICCS affect the upwelling jet that runs southwards along the western coast of Portugal, eventually reaching Cape St. Vincent (37\({}^{\circ}\)1'30\" N, 8\({}^{\circ}\)59'40\" W). As a consequence, the heterogeneous behaviour of the upwelled water gives rise to a variety of patterns that can be seen in the SST satellite images. In particular, experts visually inspected the SST datasets to determine a set of recurring temperature trends that are consistently observed throughout the considered time span and identified four main patterns relative to four types of mesoscale events:  
1. A filament of cold water originating from the upwelling jet, going westwards;
2. A filament of cold water going southwards, extending the upwelling jet beyond Cape St. Vincent;
3. A stream of cool water that bends eastwards from the upwelling jet, overtaking Cape St. Vincent and running along the southern coast of the Iberian peninsula;
4. A warm countercurrent originating in the Gulf of Cadiz and running westwards along the southern Iberian coast, eventually reaching Cape St. Vincent and turning northwards.  
These four patterns, and the corresponding mesoscale events, will be called E1, E2, E3, and E4, respectively. To be more precise, pattern E3 presents two subcases: E3i, when the difference in temperature between the cool stream and the waters of the Gulf of Cadiz is small, mostly occurring during winter; and E3u, with a more pronounced thermal gradient. In this analysis, we do not distinguish between these two cases. Figure 2 shows some examples of the described patterns, where the images on the right refer to the same coordinates as in Figure 1.  
Starting from this classification, a labelled dataset of SST images has been obtained, in which expert oceanographers manually assigned a label \"E1\"-\"E4\" to each image in which a clear pattern could be seen (no label was assigned if no pattern could be recognised).  
This dataset constitutes the ground truth for all the subsequent analysis; it is a _static_ dataset, meaning that the information about the time at which an image has been generated has mostly not been taken into account when a label was assigned. However, MEC exploits also the _dynamic_ information contained in the SST patterns. To help us visualise this information, the multiple SST signals contained in satellite data with timestamps belonging to a given time interval and related to a given geographical area are extracted from the corresponding data files and arranged in a single 2D time-SST plot, namely a _spaghetti plot_ (see Figure 3d below). This way it is possible to assess the SST temporal trends in the selected area. In the next section the process of the spaghetti plot generation is described more in detail.  
All the software dedicated for this analysis has been developed within a Python framework.  
Figure 1: Example of a bad quality satellite image.
## 2 Literature Review
### Autonomous Vehicles (AV)
#### 2.1.2 Expected Benefits and Challenges of AV  
The potential benefits AVs can provide largely depend on the level of automation [18]. As machine learning technologies are getting more and more reliable, it is helping to create an absolute artificial intelligence system. That is, a system which is not only capable of making decisions, but right decisions on right time. This technology when applied to cars create remarkable road vehicles which are capable of using these machine learning algorithms to drive themselves from one point to other, solving multi-level challenges and making several spontaneous right decisions [19]. According to [PERSON] [20] and [PERSON] et al. [21], it is predicted that autonomous vehicles will escalate convenience and safety of travelers, reduce hindrance caused by congestion and limit fuel consumption. Further, [PERSON] [1]  
Figure 1: Levels of vehicle automation by NHTSA [15; 16].  
highlights that AVs have a potential to significantly reduce costs of dynamically scheduled services and individual car ownerships, as more and more people drift towards using the shared cars model for commuting or travelling. It would also eliminate the performance limitations of the human driver. Moreover, [PERSON] and [PERSON] [3] proposed that AV operations are inherently different from human-driven vehicles. AVs will be configured to follow traffic laws, have lesser reaction time, control the flow of traffic, improve fuel economy and reduce emissions. Autonomous vehicles can even be made to gauge the breaking and acceleration decisions of surrounding vehicles to avoid congestion and drastically reduce road accidents. Several studies conclude that a pivotal impact of autonomous vehicles would be reduced congestion, increased road safety and an increased highway capacity as discussed by [PERSON] et al. [11], [PERSON] et al. [22] and [PERSON] [23]. [PERSON] et al. [21] further added that road capacity could be enhanced by AVs improving driving behavior relating to time gaps, speed and lane changes. Another weighty benefit AVs can provide is the much-needed mobility solution for the elderly and disabled people, which is also note-worthy [3].  
An autonomous vehicle may easily administer common road situations. However, to design a system that can perform safely in every situation is a very challenging task. Some research also concludes that autonomous vehicles can be an easy target for cyber-crimes, vandalism and passenger security issues that might also arise as shared mobility comes into play and several studies agree that AVs would be very difficult to regulate [3; 14; 20; 23; 24]. Apart from technological maturity and reliability, concerns about liability and insurance challenges in case of failure of onboard systems or an accident, are some of the biggest hindrances in the diffusion of AVs with existing laws and regulations. There is an ongoing debate regarding who should be held responsible in case of an accident--the owner or the user of the AV [14; 23; 24].
# Multi-User Scheduling for 6G V2X Ultra-Massive MIMO System
## 3 Ultra-Massive MIMO Multi-User Scheduling Based on BD Precoding  
The BD algorithm has been widely studied in ultra-massive MIMO systems, but it does not consider the channel correlation and channel conditions. The user scheduling algorithm with the optimal channel correlation is the exhaustive method, which traverses the user set to be selected and selects the user with the lowest correlation. The channel correlation cannot be used as the only criterion for selecting the optimal user set. It also needs to consider the quality of the user's own channel conditions, because the user's own channel conditions are also a key factor for the system. Therefore, an ultra-massive MIMO multi-user scheduling algorithm based on channel correlation and channel conditions under BD precoding scheme is proposed.
# Communication Fault Maintenance Decision of Information System Based on Inverse Symmetry Algorithm
## 4 Discussion
### Information System Communication Technology Troubleshooting Measures
#### 4.3.2 Improve the Security System  
Combined with the effective application of information system communication technology, in order to better improve its running fluency and reliability, it also needs to focus on the continuous updating and improvement of the software system, so as to ensure it has the ideal security and integrity effect and solve various possible loopholes or unreasonable configuration problems. In view of all kinds of security threats existing in the application of the above information system communication technology, it is necessary to ensure that its security assurance system is more comprehensive and appropriate, and is able to be continuously updated and maintained. It fills in all kinds of potential security vulnerability threats, does a good job in the maintenance and repair of network security, and makes its overall operation smoother. In addition, in order to better improve the effect of its security, we can also effectively strengthen it with the help of firewall technology, so that the application of firewall technology can form an ideal security effect in the whole network environment, realize the comprehensive coverage and effective separation of the information system, and avoid the possible threat and interference. With the continuous innovation and development of current software technology, in order to better improve the security and guarantee effect of communication, the reasonable use of encryption technology is also an important part, which can realize the encryption protection of key information, avoid the threat of some information leakage or theft, and finally improve the communication security level of information systems.
# XBeats: A Real-Time Electrocardiogram Monitoring and Analysis System
## 2 Background and Related Work  
The prevalence of chronic illnesses is increasing. Currently, developments in wearable sensors and communication protocols contribute to the system's enrichment in ways that will soon transform healthcare services. The first of these improvements is remote patient monitoring (RPM). RPM systems collect vital signs from patients by non-invasive procedures and their real-time transmission to healthcare providers. The information collected by RPM devices may assist clinicians in making the best choice possible at the appropriate moment. Therefore, many efforts have been conducted to advance remote ECG monitoring systems to match or exceed the performance of the ECG testing administered at hospitals and healthcare facilities [8]. This section intends to identify research gaps in defining the lifecycle required to perform a standard ECG monitoring system and highlight the solutions introduced in the literature. The section is divided into three topics categorized by the number of ECG leads provided in each work and an additional section evaluating the work introduced in the industry from a commercial perspective.
# Comparing Monitoring Networks to Assess Urban Heat Islands in Smart Cities
## 4 Location and Installation of the Measuring Devices
### Bespoke Network  
In this section, the procedure for establishing the location and installation of the AWSs is described, which is necessary for communication devices for the deployment of the network, since smart city communication networks have been used. The locations of the AWSs were determined jointly to guarantee the representative nature of the UCZ and the uniformity of the data, following the recommendations of the WMO.