esa-sceva/satcom-chunk-collection huggingface dataset:
# A New Method for Large-Scale Landslide Classification from Satellite Radar
## 2 Materials and Methods
### Case Study: The 2015 Gorkha Earthquake
#### 2.2.3 ROC Analysis  
A common problem in classification is the choice of threshold at which to assign classes given a continuous classifier. This choice of threshold is strongly dependent on the user requirements and their relative tolerance for false positives and false negatives and so it is preferable to test the performance of a classifier before setting this threshold. We therefore used Receiver Operating Characteristic (ROC) analysis to test the landslide detection ability of each of the three classification surfaces described in Section 2. ROC curves are commonly used to measure the ability of a continuous classifier to correctly identify a binary array [46], in this case, a map of landslides and non-landslide pixels. For a range of classifier threshold values, the true positive rate (the fraction of mapped landslide pixels that are correctly classified as 'landslide') is plotted against the false positive rate (the fraction of mapped non-landslide pixels that are incorrectly classified as 'landslide'). As the threshold is relaxed from a value where all pixels are classified as 'non-landslide' to one where all are classified as 'landslide', a good classifier will identify true positives at a faster rate than it accepts false positives. The ROC curve plots the true positive rate against the false positive rate, with better classifiers resulting in a curve that lies closer to the upper left-hand corner of the plot. The overall performance of a classifier can therefore be quantified by the area under the curve (AUC). For a random classification surface where any pixel has a 50% chance of being classified as landslide or non-landslide, the ROC plots as a straight line between (0,0) and (1,1) with AUC = 0.5. A classifier AUC is expected to lie between 0.5 and the perfect case, for which AUC = 1.0.
# An Overview of GEO Satellite Communication Simulation Systems
## 2 Coverage Analysis  
Coverage analysis plays a fundamental role in the design and evaluation of satellite communication systems. Accurate coverage assessment depends on multiple key modeling components, including satellite orbital parameters, antenna gain patterns, beam geometry, and environmental factors such as terrain elevation and atmospheric conditions. These elements collectively determine the spatial and temporal accessibility of satellite beams. To evaluate coverage performance, metrics such as accessibility (i.e., line-of-sight visibility, minimum elevation angle, and obstruction status), service time, spatial distribution (i.e., coverage footprint, blind zones, and overlapping regions), and Quality of Service (QoS) (i.e., signal-to-noise ratio (SNR), throughput, and link reliability), are commonly used. To support the planning, evaluation, and optimization of satellite communication systems, a variety of coverage analysis methods have been developed. These methods differ significantly in terms of modeling complexity, computational efficiency, and adaptability to dynamic environments. In this section, we categorize and review the representative coverage analysis approaches into four main classes: geometry-based methods, fast evaluation and approximate inference techniques, simulation-based modeling, and data-driven adaptive approaches.
## 2 Current Status of GNSS Integrity Service
### Development Trends in GNSS Integrity Services
As for GLONASS, Russia has initiated the Federal Special Program for GLONASS from 2021 to 2030, aiming to enhance the reliability and accuracy of the GLONASS constellation. As a part of this program, Russia plans to launch multiple GLONASS-K2 satellites before 2030 to improve the reliability of the GLONASS constellation. In addition, Russia intends to launch six GLONASS-V satellites operating in high elliptical orbit (HEO) to enhance navigation accuracy and reliability in Russia and its surrounding areas. As a backup solution for GLONASS-V, Russia is also considering using LEO satellites to enhance the performance of the GLONASS constellation. Based on the information above, the development trends in GNSS integrity services are summarized as follows: firstly, the SAIM technique is an important approach to improve navigation integrity, which has been considered by the BDS-3, GPS, and Galileo. Secondly, it has become a hot topic to augment GNSS integrity with LEO satellites. LEO satellites enhance integrity from the service domain perspective. On one hand, they achieve multiple redundancy monitoring of medium- and high-orbit satellites, which reduces the false alarm and missed detection rates in integrity monitoring. On the other hand, by broadcasting navigation enhancement signals, LEO satellites increase the number of satellites visible to users and improve the geometric configuration. This enhancement improves users' positioning accuracy and reduces the required level of protection for integrity. In the upcoming 5 to 10 years, GNSS service providers will focus on the development of next-generation GNSS constellations and the development of LEO constellations. Therefore, the future development of the BeiDou system may need to consider both advanced SAIM techniques and LEO-based integrity augmentation so as to effectively improve BeiDou's integrity performance.
## 7 Conclusions  
In this paper, we proposed a Secure Cluster-based Multipath Routing protocol (SCMR) for WMSNs designed to handle the additional requirements of reliable data delivering of different traffic classes and  
Figure 11: Density of Cluster Heads vs Network Size.  
provide load balancing by using multipath routing. The proposed routing protocol, SCMR, is based on the hierarchical structure of multiple paths established depending on the hop count and received signal strength as an indication on the link quality, delay, and distance between the nodes. SCMR maintains minimum end-to-end delay suitable for real-time and non-real-time data packets to meet their playout deadline, and achieves high throughput and packet delivery ratio by selecting the paths with better link quality and avoiding collisions and interferences. SCMR reduces energy consumption at sensor nodes by moving the multimedia processing complexity as well as the aggregation process to the cluster heads' side along with preventing path loops and path cycles in establishing the routes. Also we presented a light-weight distributed security implementation of key management for supporting a secure communication among the nodes. Performance evaluation results show that SCMR clearly outperforms the preexisting ones (DHCT, MCRA, EDGE) in all average end-to-end delay, throughput, packet delivery ratio and battery power consumption. In future work, we will consider a cross layer design optimization especially between the routing and MAC layers to maximize the overall network performance with minimum energy consumption, reliable delivery, and efficient resource management. Also with respect to the security scheme, we will develop a light-weight intrusion detection system to eliminate the threats from insider attacks.
# The Customized Automatic Processing Framework for HY-2A Satellite Marine Advanced Products
## 4 Case Studies  
In order to validate the feasibility and functionality of the HY-2A CAPF, a set of predefined algorithms were developed. In this paper, a set of experiments were conducted to demonstrate the performance of the framework. These experiments represent the typical geophysical products that users want to generate.
## 5 Data Communication Phase
### Intra-Cluster Transmission
#### 5.1.2 Multi-Hop
Transmission of data from N\({}_{1}\) to N\({}_{3}\) through N\({}_{2}\) reduces the total energy consumption only if the given condition in Equation (25) is satisfied. In other words, the minimal hop path may not be the minimal cost path:  
\[\mathrm{E(N_{1}N_{3})+E(N_{3}N_{2})<E(N_{1}N_{2})} \tag{25}\]  
The selection between multi-hop and single-hop communication of cluster members with CH is done based on the size of the cluster in [127]. The paper defines a critical cluster size (Q\({}_{\mathrm{critical}}\)) threshold, which is calculated by CHs according to the network parameters such as number of nodes, size of the network area, number of CHs, transmission energy and energy consumption in data aggregation process (E\({}_{\mathrm{DA}}\)). The critical value of the square area size of a single cluster is presented in Equation (26):  
\[Q_{critical}\ =\frac{E_{TX}\ +(1\ /\ P_{CH}\ -1)(\ E_{RX}\ +\ E_{DA}\ )}{e_{f_{S}}\ \{P_{CH}\ -1-1\ /\ \pi+(1-P_{CH}\ )/(2\pi P_{CH}\ )\}} \tag{26}\]  
Each CH calculates the approximate size of the cluster area and if it is smaller than Q\({}_{\mathrm{critical}}\), single-hop communication is implemented; otherwise CH implements the shortest path tree (SPT) within the cluster and cluster members use the routing path to send data packets to the CH.
# Seismic Responses of a Cable-Stayed Bridge with Consideration of Uniform Temperature Load
## 2 Description of the Prototype Bridge  
The prototype bridge [22] has been chosen in this work based on an existing cable-stayed bridge in the northwest of China. The bridge has two symmetrical pylons, and a total span of 742 m with a main span of 430 m and a side span of 156 m, as show in Figure 1a. The cables are arranged in two inclined planes with 68 cables in each plane. The semi-fan cable system was adopted due to its efficiency for long span cable-stayed bridges. A concrete deck and steel deck are respectively used in the side span and main span of the bridge, which will not only decrease the dead load of the main span, but also increase the dead load of the side span. Thus, the stiffness of the whole bridge will be enhanced.  
The modified A-shaped pylons of the bridge with total height of 150 m consist of an A-shaped component on the upper part and a wall in the lower part, as can be seen in Figure 1b. The hollow sections of the pylons are made up of concrete, which can save the costs of the pylons' erection and maintain the whole stiffness of the pylons at same time. The longitudinal deformation of the deck is assumed to be partly restrained at each pylon. That is to say, bearings are attached in the bridge to connect the deck and pylons. Therefore, the relative movement between the deck and the pylons will happen when the shear force in the longitudinal direction exceeds the yield force of bearings.
Furthermore, when integrated with Geographic Information System (GIS) platforms, PS-InSAR outputs can provide valuable insights into the relationship between subsidence patterns and local geotechnical, hydrological, and infrastructural factors, enabling more comprehensive and data-driven decision-making for railway asset management [23]. Although PS-InSAR has been widely applied to urban deformation and geological hazard monitoring, its implementation in high-speed railway networks--where high precision and reliability are essential--remains limited due to technical challenges and insufficient validation efforts [22]. To address these limitations, this study applies PS-InSAR techniques to monitor ground deformation along the Honam High-Speed Railway,a corridor known for soft-ground conditions and long-term subsidence risks. A total of 29 high-resolution TerraSAR-X and TanDEM-X images spanning a three-year period were utilized to ensure the accurate detection of millimeter-scale displacement. Therefore, the objective of this study is to apply PS-InSAR techniques to monitor ground deformation along the Honam High-Speed Railway and assess the feasibility of satellite-based remote sensing for long-term infrastructure maintenance. By analyzing multi-temporal SAR datasets and validating the results through comparison with ground-based measurements, this research aims to identify critical areas of subsidence and demonstrate the advantages of PS-InSAR for high-speed railway monitoring. The findings contribute to the development of scalable, cost-effective monitoring strategies that support preventive maintenance and ensure the structural safety of railway systems in geotechnically unstable regions.
# Evaluation of Green Strategies for Prolonging the Lifespan of Linear Wireless Sensor Networks
## 3 Classification of Energy Management Techniques for Prolonging WSN's Lifetime
### A Review of Taxonies for Classifying Energy Management Techniques in WSN
The energy-harvesting techniques aim to increase the energy available to the nodes by scavenging energy from the external environment such as solar, wind, vibrations, radio frequency, thermal, etc. The energy transfer/charging techniques aim to extend the lifetime of the WSN by engaging in wireless energy transfer from energy-rich nodes to energy-deficient nodes. [PERSON] et al. [57] broadly classified energy-saving methods into hardware-based and algorithmic-based energy-saving methods. The hardware-based methods encompass techniques like low-power sensors, low-power processors, low-power transceivers, energy harvesting,and wireless energy transfer. The algorithmic-based methods encompass techniques like data-driven approaches, duty cycling, and energy-efficient routing. The studies of [62; 66] classified energy management techniques for prolonging the WSN into two main groups: energy consumption and energy provision. According to the author, the former focuses on the operations and devices that deplete energy through performing transmission, reception, and data processing, whereas the latter intends to discover different methods for supplying the sensor node with the required energy source in order to allow the WSN to operate for as long as possible. From their taxonomy, it can be seen that the energy consumption schemes consist of energy-saving techniques (duty cycling and data-driven) and energy-balancing techniques (mobility-based), while the energy provision schemes involve energy-scavenging techniques (harvesting) and energy-balancing techniques (transference).
###### Abstract  
This paper presents a WENO-based upwind rotated lattice Boltzmann flux solver (WENO-URLBFS) in the finite difference framework for simulating compressible flows with contact discontinuities and strong shock waves. In the method, the original rotating lattice Boltzmann flux solver is improved by applying the theoretical solution of the Euler equation in the tangential direction of the cell interface to reconstruct the tangential flux so that the numerical dissipation can be reduced. The fluxes at each interface are evaluated using a weighted summation of lattice Boltzmann solutions in two local perpendicular directions decomposed from the direction vector so that the stability performance can be improved. To achieve high-order accuracy, both fifth and seventh-order WENO reconstructions of the flow variables in the characteristic spaces are carried out. The order accuracy of the WENO-URLBFS is evaluated and compared with the traditional Lax-Friedrichs scheme, Roe scheme, and the LBFS by simulating the advection of the density disturbance problem. It is shown that the fifth and seventh-order accuracy can be achieved by all considered flux-evaluation schemes, and the present WENO-URLBFS has the lowest numerical dissipation. The performance of the WENO-URLBFS is further examined by simulating several 1D and 2D examples, including shock tube problems, Shu-Osher problems, blast wave problems, double Mach reflections, 2D Riemann problems, K-H instability problems, and High Mach number astrophysical jets. Good agreements with published data have been achieved quantitatively. Moreover, complex flow structures, including shock waves and contact discontinuities, are successfully captured. The present WENO-URLBFS scheme seems to present an effective numerical tool with high-order accuracy, lower numerical dissipation, and strong robustness for simulating challenging compressible flow problems.  
finite difference method; WENO; lattice Boltzmann; rotated scheme; low dissipation +
Footnote †: journal: applied sciences
# The Fusion of MRI and CT in the Planning of Bracotherapy for Cancer of the Uterine Cervix
## 4 Discussion  
Due to the average reduction in the CTV by 28% during EBRT before starting IGABT, it is not possible to plan an adaptive CTV based on the pretherapeutic MRI 1. To use an MRI for adaptive planning, a second MRI is mandatory, preferably in the fifth week of EBRT.  
Although CTVs have larger outlines in the CT due to the diagnostic uncertainty, after carefully merging the images in planning software, only 80.8% of the CTV was defined precisely in MRI 2. If the IGABT had been planned exclusively according to the MRI 2-Scan, 19.2% of the CTV would not have been hit. The planning of IGABT on the basis of MRI 2, therefore, does not reach sufficient coverage of the tumor according to the image fusion, when the CT was acquired with a vaginal applicator and the MRI was acquired without.  
Figures 1-3 show that the uterus is often straightened, erected, and cranially shifted by the insertion of a vaginal applicator. These anatomical changes in the configuration of the uterus clearly caused the insufficient results of the CT and MRI image fusion in our study. Planning brachytherapy exclusively on the basis of an MRI can therefore only be carried out on an MRI with the vaginal applicator system in situ to enable good irradiation of the CTV and, at the same time, protection of neighboring organs at risk. The beginning of this practice has already been described in older methodological works, which, although they used image fusion, have not yet provided for the 3D volumetric planning of radiation dose application [6; 8; 22]. In order to use the automatic fusion of MRI and CT [23], these anatomical changes must be taken into account. That is why a vaginal applicator in situ cannot be dispensed with in scanning MRI.  
Figure 1: A uterus straightened by the insertion of the vaginal applicator.  
The superior delimitability of tumors in Gadolinium contrast-enhanced MRI described by [PERSON] [24] could not be confirmed as useful for merging images by the small number of cases of our study. Although an implanted Smit sleeve improved the anatomical orientation and shape of uterus, its usage did not lead to superior results of the image fusion in our study. Neither implantation of the Smit sleeve nor use of Gadolinium contrast in MRI 2 could compensate for anatomical mismatch caused by missing vaginal applicator in MRI.  
However, even without automatic fusion, the diagnostic information of MRI is indispensable [8]. Sufficient experience about suitable MRI sequences is described in other studies [12; 25].  
Figure 3: A uterus cranially shifted by the insertion of the vaginal applicator.  
Figure 2: A uterus erected by the insertion of the vaginal applicator.
## 3 Dependability
### Reliability  
The complexity of distributed edge networks means that achieving reliability in such an environment is not an easy task. With the increasing number of MCAs solutions on the market, requirements for reliable systems are indispensable, and furthermore, still a challenge to achieve. Rapid changes in computing environments also bring challenges to reliability, for example, asynchronism, heterogeneity of software/hardware, scalability, and fault tolerance, to mention some. In [28], the authors briefly explored reliability issues in edge AI systems and proposed an architecture that meet latency and reliability requirements for many MCAs. It is identified that computation on edge systems occur in three different layers: bottom (end devices), middle (servers), and top (centralized cloud). In order to achieve good communication and a fast response, all three layers must be properly synchronized, like the storing and data access for processing [13].
## 5 Experimental Results  
This section explains corresponding results and corresponding analysis to answer each of the research questions.  
RQ1: How Much Can Harmony Search (HS)-Based Parameter Optimization Improve Software Defect Prediction (SDP) Performance in Maritime Domain?  
Table 7 shows how much the HS-based parameter optimization can improve the prediction performance, answering RQ1. The best performance values in the table are indicated in bold face.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline HMS & 10,000 \\ \hline HMCR & 0.75 \\ \hline PAR & 0.5 \\ \hline FW & 0.25 for continuous variable \\  & 10 for discrete variable \\ \hline MI & Adjusted \\ \hline \hline \end{tabular}
\end{table}
Table 6: Hyper-parameter values of harmony search.  
The datasets A and B were preprocessed by adjusting the class ratio in 5 steps (i.e., 100:20. 100:40, 100:60, 100:80, 100:100) before parameter optimization. Once again, the reason for the pre-processing of changing the class ratio between defects and non-defects was to show that this approach can be covered in various data distributions of maritime domain. In the table, DT indicates decision tree only, DT+BG indicates decision tree and bagging together, and DT+BG+HS indicates decision tree and bagging with HS-based parameter optimization.  
Compared to DT and DT+BG, the balance which reflects PD and PF showed that in all cases, DT+BG+HS produces the best performance. For dataset A, in the case when the ratio between the majority and minority classes is 100:100, the best PD and B are 0.95 and 0.94 with HS-based parameter optimization. For dataset B, when the ratio between the majority and minority classes is 100:80, the best PD and B are 0.99 and 0.97. As a result of the effect size test, the difference was significant beyond the medium size.  
Compared to previous case study [14], HS-based parameter optimization showed higher performance results at all ratios. The results showed that in the class imbalance ratio between defect and non-defect is high (e.g., A1, A2, B1), more performance improvement was observed through parameter optimization. The significant differences beyond medium size were underlined in the table. On the other hand, there was improvement of small effect in the dataset with low class imbalance ratio (e.g., A3, A4, A5, B2, B3, B4, and B5), which already showed high performance of defect prediction through the oversampling technique [29]. Thus, this approach will have a greater effect on data distribution with high class imbalance ratio.
# RSCS6D: Keypoint Extraction-Based 6D Pose Estimation
## 4 Experiments
### Comparison with the State-of-the-Art Methods  
The LineMOD dataset [41] is a widely used benchmark for 6D object pose estimation, featuring 13 objects with significant shape variation. These objects are captured in sequences that include mild occlusions, cluttered backgrounds, textureless surfaces, and varying lighting conditions, making it challenging for accurate pose estimation in real-world scenarios.  
Our approach follows the protocol established in previous works [14; 20; 27; 42], which adopts a standard 15%/85% training/test split. This setup ensures a robust evaluation of pose estimation algorithms under diverse and realistic conditions.  
Our proposed real-time pose estimation algorithm demonstrates superior performance on the LineMOD dataset, outperforming existing methods such as PVNet [14], PoseCNN [42], DenseFusion [20], and G2L-Net [27]. As shown in Table 1, our algorithm achieves an average ADD accuracy of 99.32% across 13 objects, representing a 0.6% improvement over the best baseline method, G2L-Net (98.7%). Notably, our method sets new records for 11 objects, including ape and bench vise, with perfect ADD-S accuracy of 100% for symmetric objects like eggbox and glue.  
In terms of real-time performance, our algorithm processes at 40 FPS, significantly surpassing DenseFusion (19 FPS) and G2L-Net (28 FPS). Importantly, these results are achieved without the need for refinement post-processing, leveraging the advantages of RGB-D data effectively.