esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Results and Discussion
### Underground Implementation of a Digital-Twin-Based Spatial Object Extraction Algorithm
#### 4.1.3 Planar Spatial Object Extraction Process  
RANSAC was used for extracting planar objects. This approximates the parameters of the model by ascertaining a consensus: whether the sample from the point cloud aligns with the predefined model. Using RANSAC for segmentation has benefits such as the capacity to separate the ground from objects using a planar model and isolate each object by eliminating the ground and walls. This study incorporated an algorithm that carried out segmentation to draw out wall objects.  
The procedure for extracting planar objects with RANSAC entails the following: The model is initialized to align with the virtual inliers, implying that all of the free parameters of the models are set to match those of the inliers. If sufficient points are categorized as virtual inliers, the model is considered as accurately estimated. Subsequently, the error of the inliers concerning the model is calculated to assess the quality of the model, and then the planar objects are extracted.
# SD-BROV: An Enhanced BGP Hijacking Protection with Route Validation in Software-Defined eXchange
## 5 Conclusions  
To strengthen the security of BGP route exchange, this paper proposed SD-BROV--an idea that provides BGP route validation with flexibility and alternation in SDX. For enabling such functionality, an SDX application has built in ONOS controller to check received routes and investigate them with RPKI validation. By integrating ROV with RPKI, the implemented SDX is able to provide security protection against deliberate or accidental routing events to SDX members. The experiment results also show that the developed SDX is able to detect BGP hijacking incidents as well as prevent legitimate traffic to be redirected to the misleading routing path.  
According to experiment result in the second scene, when the poisoned AS is not directly connected to the SDX, the SDX can only stop half-way in the direction of the traffic affected by the misleading route, and redirection is not going to happen because that there is no intent or datapath created. Nevertheless, there is a need to develop a monitoring mechanism in the SDX controller for preserving previous normal routes, triggering a fail-safe mitigation to keep traffic gracefully forwarding to original next-hop when detecting the attack. This improvement is planned in the future work of this research, and it is expected to provide better resilience in attack mitigation that against route poisoning in SDX. Furthermore, to investigate the issue in real-world deployment scenarios, using a large-scale environment to evaluate and improve developed systems [32] is important as well. Authors of this paper will try to find more practical ways and realistic scenarios in future evaluations.  
Conceptualization, P.-W.T. and A.C.R.; Data curation, M.H.C.; Formal analysis, M.H.C.; Investigation, P.-W.T., A.C.R., M.H.C. and S.K.P.; Supervision, T.C.L.; Validation, M.H.C. and S.K.P.; Writing--original draft, P.-W.T. and A.C.R.; Writing--review & editing, S.K.P. and T.C.L. All authors have read and agreed to the published version of the manuscript.  
This research was funded by National Central University, Taiwan.  
Data Availability StatementNot Applicable, the study does not report any data.  
**Acknowledgments:** Authors would like to thank the anonymous reviewers for their valuable comments and suggestions on this paper. This research was supported in part by the Ministry of Science and Technology of Taiwan, under Contracts MOST 109-2222-E-008-005-MY3. Authors are also grateful to TWAREN SDN research team members for their great help.  
**Conflicts of Interest:** The authors declare no conflict of interest.  
Figure 16: Ping test result in second scene.
## 2 Related Work
### Three-Dimensional Reconstruction  
Early 3D reconstruction was carried out using structure from motion, such as the colmap [17] algorithm. With the development of deep learning technology, the MVSNet [6] series, which are based on multiview reconstruction, have also appeared. MVSNet [6] is the first open-source deep learning 3D reconstruction system, and it has paved the way for multiview 3D reconstruction with depth. Based on MVSNet, RMVSNet [18] replaces 3D convolution with a GRU timing network to reduce the calculation burden and improves the prediction speed. PointMVSNet [19] first predicts the depth information of pixels and then forms a three-dimensional point cloud with the image. Then, a 3D point cloud algorithm is used to optimize the regression of the depth value. Cascade MVSNet [20] introduces a hierarchical network model that uses different depth intervals to train more data at one time. Fast-MVSNet [21] uses sparse cost volume and a Gauss-Newton layer, which greatly improves the prediction speed.  
It is clear that the MVSNet series are the neural network version alternatives to the traditional photogrammetric 3D reconstruction method. By constructing the feature and the cost volume, homomorphic transformation is carried out to simulate the image matching in the traditional photogrammetry, which still belongs to the three-dimensional reconstruction methods with a semianalytic form. Information on the surface can be located by inferring the depth of the ray after the appearance of the neural radiation field [7; 9; 10; 16; 22]. However, the aforementioned NeRF-based methods do not offer effective sampling strategies for unmanned aerial vehicle (UAV) scenes. Additionally, since NeRF solely optimizes based on radiative quantities, geometric changes in light paths can affect the input radiative quantities. Therefore, integrating geometric and structural information in conjunction with traditional photogrammetry techniques may yield better performance outcomes.
## 1 Introduction  
Red mud is a solid waste and abundantly produced from the treatment of bauxite with sodium hydroxide during Al extraction. For 1 ton of alumina extracted, approximately 1 to 2 tons of red mud residual is produced [1]. Due to its high calcium and sodium hydroxide contents, red mud is relatively toxic and causes severe environmental pollution and ecological damage [2]. Thus, safe disposal methods have been developed for red mud (including dewatering, drying, and landfilling [3]), which cause additional cost and require regular management.  
The resource utilization of red mud could solve its disposal problems [4; 5; 6; 7; 8]. Recently, research has focused on utilizing red mud for the removal of toxic heavy metals [9], phosphate [10], and harmful organics [11]. [PERSON] et al. [9] investigated the pretreatment of red mud by a combined method of CO\({}_{2}\) neutralization and calicing at 500 \({}^{\circ}\)C, and found that the pretreated red mud showed high adsorption capacity of Zn\({}^{2+}\) (14.9 mg/g). [PERSON] et al. [10] reported that after hydrochloric acid neutralization, the neutralized red mud exhibited higher adsorption capacity for phosphate (108.6 mg/g) than untreated red mud. However, the separation process of red mud from water after adsorption, including high-speed centrifugation, precipitation, coagulation and/or filtration [5; 9; 10], was tedious, which limited its application for wastewater treatment. An optimal method to rapidly separate red mud from water was to convert weakly magnetized red mud into magnetically separated adsorbent.  
The Fe oxides in red mud can be converted into magnetic magnetite after roasting under addition of pyrite [12], coal [13], or by injecting H\({}_{2}\)[14] and methane [15]. [PERSON] et al. [12] reported that part of the Fe oxides in red mud was converted into magnetite with pyrite as exogenous ferrous and reducing reagent after calcination at 600 \({}^{\circ}\)C. [PERSON] et al. [14] reported that 87% of the hematite (Fe\({}_{2}\)O\({}_{3}\)) in red mud was transformed into magnetite after roasting at 480 \({}^{\circ}\)C using H\({}_{2}\) as reductant. However, high temperatures were applied in these methods to promote the breakdown of the Fe-O-Si or Fe-O-Al bonds into the form of Fe-O-Fe linkage [16]. The breakdown of Fe-O-Si or Fe-O-Al bonds can be achieved at low temperature [17]. For instance, by adding iron powder, red mud could be converted to magnetite-containing materials after hydrothermal treatment at 260 \({}^{\circ}\)C [18]. However, the obtained magnetite was probably generated from the oxidation of iron powder. Iron-bearing minerals, such as andradite and hematite [6], were abundant in red mud, and can be converted into magnetic minerals by adding reductants under mild condition. However, the phase transformation of Fe-bearing minerals in red mud has not yet been studied.  
In this study, red mud was converted into magnetic adsorbent via a facile hydrothermal route using ascorbic acid as reductant. To demonstrate the potential applications of red mud, the ability of the synthesized magnetic adsorbent to remove Zn\({}^{2+}\) from water was investigated.
# Topology Optimisation in Structural Steel Design for Additive Manufacturing
## 3 Topology Optimisation--One Concept, Various Fields
### Structural Optimisation and Topological Optimisation in the Context of Structural Steel Design  
Structural Optimisation and Topological Optimisation concepts have been used with increasingly unrestrained freedom, even in Academia. Thus, it may be helpful to mention that the most rooted nomenclature employs Structural Optimisation as an umbrella for Topology Optimisation, on the one hand, and Shape and Size Optimisation, on the other hand [44; 160]. In the context of Structural Steel Design, while seldomly, the use of Structural Topology Optimisation (STO) has been reported [139], referring to TO in this specific field.  
Conceptually, Shape and/or Size Optimisation is easy to define, considering its scope, limited to variables as cross-sectional properties, member types and geometry, and rigidly constrained by predefined configurations. In simple terms, Topology cannot be changed and, therefore, this concept is deemed to improve an existing design, in which it very much depends on closeness to optimal.  
Topology Optimisation, also named Layout Optimisation by some pioneers, bears the capacity for topological modification. In other words, it is unrestricted in its ability to create voids or add material in the design domain and act upon the structure's connectivity. That said, it is relatively straightforward that TO contains and exceeds the Shape and Size Optimisation and therefore, fulfils all the possible Structural Optimisation scopes.  
It should be highlighted that TO is not constrained to materially homogenous volumes. It may be employed as heterogeneous, including composite or microstructurally designed materials, but also in grid-like \"ground structures\", made of one-dimensional elements.  
In practical terms, differences are significant not so much between concepts, but mostly between applications and engineering fields. Concerning structural steel design, the Size, Shape, and Topology Optimisation can be graded into an intervention freedom continuous scale. The practical constraints and one-dimensional members design may limit optimisation to size and shape, even if the possibility for adding or suppressing members in a predefined configuration is available. The optimisation of continua, either in small volumes as joints or macro elements, as a building or bridge geometrical envelope, find a most suitable tool in TO.
## 4 Results
### Relevance Analysis  
Table 8 shows the accuracy after removing each feature (one by one) from the proposed approach. It can be observed that after removing the feature 'variance of area of triangles', the accuracy of the approach degrades significantly on the Boston University dataset, which shows high contribution of this feature. Similarly, the accuracy becomes lowest when 'area of triangle' is removed from the proposed approach using DrivFace and Pointing '04 datasets.
# A Segmentation-Based Optimal Seamline Generation Method for SAR Image Mosaic
###### Abstract
Then, under the constraint of homogeneous areas, the cost matrix is constructed by combining the intensity information of pixels. Finally, a shortest path search algorithm is employed to determine the optimal seamline within the cost matrix. This comprehensive method enhances the seamlessness of SAR mosaic images, considering the unique characteristics and challenges posed by SAR data. The SAR mosaic results with complete ground objects are helpful for subsequent image interpretation and analysis. The main contributions are as follows:  
1. Introducing a SOSG method, this method is designed to identify optimal seamlines between SAR images, enhancing the seamlessness of the resulting mosaic and the integrity of ground targets. 2. The method incorporates a joint segmentation technique and a clustering method for SAR images. This method forms the foundation for effectively classifying areas within SAR images as either homogeneous or non-homogeneous, providing a valuable basis for subsequent processing steps. 3. Notably, the proposed SOSG method demonstrates an improvement in the quality of SAR image mosaics when compared to existing methods. This signifies the effectiveness and potential advancements introduced by the proposed method in the field of SAR image processing. The forthcoming sections of this paper are structured as follows. The relevant theories and proposed framework are introduced in Section 2. The experimental results are demonstrated and analyzed in Section 3. The conclusion can be found in Section 4.
# Electromagnetically Driven Robot for Multipurpose Applications
###### Abstract  
This paper presents a novel design of a continuum robot driven by electromagnets and springs, offering enhanced precision in multi-degree-of-freedom bending for diverse applications. Traditional continuum robots, while effective in navigating constrained environments, often face limitations in actuation methods, such as wire-based systems or pre-curved tubes. Our design overcomes these challenges by utilizing electromagnetically driven actuation, which allows each segment of the robot to bend independently at any angle, providing unprecedented flexibility and control. The technical challenges discussed emphasize the goals of this work, with the main aim being to develop a motion control system that uses electromagnets and springs to improve the accuracy and consistency of the robot's movements. By balancing magnetic and spring forces, our system ensures predictable and stable motion in 3D space. The integration of this mechanism into multi-segmented robots opens up new possibilities in fields such as medical devices, search and rescue operations, and industrial inspection. Finite element method (FEM) simulations validate the efficiency of the proposed approach, demonstrating the precise control of the robot's motion trajectory and enhancing its operational reliability in complex scenarios.  
robotics; electromagnetics; continuum robot; actuators; multi-degree-of-freedom robots; 3D; electromagnetic force; solenoid Article
# Slicing on the Road: Enabling the Automotive Vertical through 5G Network Softwarization
## 3 5G-V2X Network Slicing Architecture
### Interfaces  
Four interfaces are defined within the MANO layer to facilitate slice orchestration and management, as shown in Figure 2.  
* Interface \(I_{1}\). First, information about the available computing resources are exposed through such interface by the Infrastructure Manager to each Slice Manager. Second, it serves the configuration of such resources as demanded by each Slice Manager.
* Interface \(I_{2}\). It serves the monitoring of available network resources per slice, as tracked by the SDN Controller, and the specification of network requirements by each slice.  
Figure 3: SDN architecture with main network applications (**left**) and MEC server deployment (**right**).  
Figure 2: Network slicing framework and slice instantiation for cooperative driving services.  
* Interface \(I_{3}\). It exposes the per-slice requirements to the Slicing Orchestrator and the decision about reserved resources to each slice.
* Interface \(I_{4}\). It allows the Slicing Orchestrator to interact with its peers of other MNOs.  
Concerning the interfaces between other modules in the architecture, the proposal relies on the off-the-shelf 5G service-based architecture and the open APIs already provided there.
# Experimental Study of Accuracy of High-Rate GNSS in Context of Structural Health Monitoring
###### Abstract  
Global Navigation Satellite Systems (GNSS)-based technologies have become an indispensable part of current structural health monitoring (SHM) systems because of the unique capability of the GNSS technologies to provide accurate real-time displacement information. GNSS equipment with a data sampling rate of up to about 20 Hz has been widely used for this purpose. High-rate GNSS systems (typically up to about 100 Hz) offer additional advantages in structural health monitoring as some highly dynamic civil structures, such as some bridges, require high-rate monitoring data to capture the dynamic behaviors. However, the performance of high-rate GNSS positioning in the context of structural health monitoring is not entirely known, as studies on structural monitoring with high-rate GNSS positioning are very limited, especially considering that some of the satellite systems just reached their full constellations very recently. We carried out a series of experiments with the help of a shaking table to assess the SHM performance of a set of 100 Hz GNSS equipment and three commonly used GNSS positioning techniques, PPP (precise point positioning), PPP-AR (precise point positioning with ambiguity resolution), and RTK (real-time kinematic). We found that the standard deviations of the 100 Hz GNSS displacement solutions derived from PPP, PPP-AR, and RTK techniques were 5.5 mm, 3.6 mm, and 0.8 mm, respectively, when the antenna was in quasi-static motion, and about 9.2 mm, 6.2 mm, and 3.5 mm, respectively, when the antenna was in vibration (up to about 0.7 Hz), under typical urban observational conditions in Hong Kong. We also found that the higher a sampling rate is, the lower the accuracy of a measured displacement series is. On average, the 10 Hz and 100 Hz results are 5.5% and 10.3%, respectively, noisier than the 1 Hz results.  
high-rate GNSS: structural health monitoring: PPP, PPP-AR; RTK 20221449899. [[https://doi.org/10.3390/rs141949899](https://doi.org/10.3390/rs141949899)]([https://doi.org/10.3390/rs141949899](https://doi.org/10.3390/rs141949899))
# An Early Investigation of the HHL Quantum Linear Solver for Scientific Applications
## 5 Scientific Applications and Evaluation
### Heat Transfer Problem in Climate Projection
#### 5.2.2 Performance and Resource Evaluations  
The coefficient matrices are Hermitian by design, so we only need to expand the dimension to the nearest power of 2, i.e., 16 and 32. After dimension expansion, the coefficient matrices have sparsity 82.81% and 88.28%, respectively. Both matrices have condition number 1, and all of their eigenvalues are around 1.  
When \(n_{d}=4\), gate counts in Tables 5 and 7 have almost the same numbers of circuit depths and gate counts. However, if we compare across different \(n_{d}\) in Table 7, significant increases appear in depths and all gate counts. This situation reflects one of [PERSON]'s concerns in [74] about the efficiency and the cost of data reading in quantum linear solvers. Furthermore, similar to the scenario in Section 5.1, the incremental of \(n_{c}\), despite being very costly, has a limited contribution towards reducing errors, as shown in Figure 6.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline
**Dim.** & \(n_{d}\) & \(n_{c}\) & **Depth** & **\# of Gates** & **\# of 2-Qubit Gates** & **\# of Gates After Fusion** & **Reduction from Fusion** \\ \hline \(9\times 9\) & 4 & 3 & 30,742 & 40,290 & 14,315 & 8445 & 79.04\% \\ \(9\times 9\) & 4 & 4 & 65,824 & 86,262 & 30,651 & 18,061 & 79.06\% \\ \(9\times 9\) & 4 & 5 & 135,986 & 178,180 & 63,315 & 37,284 & 79.08\% \\ \(9\times 9\) & 4 & 6 & 276,308 & 361,980 & 128,631 & 75,718 & 79.08\% \\ \hline \(25\times 25\) & 5 & 3 & 133,966 & 175,253 & 62,546 & 37,147 & 78.80\% \\ \(25\times 25\) & 5 & 4 & 287,134 & 375,643 & 134,046 & 79,547 & 78.82\% \\ \(25\times 25\) & 5 & 5 & 593,948 & 777,069 & 277,230 & 164,338 & 78.85\% \\ \hline \end{tabular}
\end{table}
Table 7: Depths and gate counts of HHL circuits for heat transfer problems.
# Observational Analysis of Variation Characteristics of GPS-Based TEC Fluctuation over China
## 2 Methods and Data Processing  
In 1997, [PERSON] et al. [11] proposed the rate of the TEC index (ROTI, in TECU/min) to describe the measurements of ionospheric irregularity and scintillation activity. The rate of TEC (ROT, in TECU/min) is measured by utilizing dual-frequency GPS observation phase data, and computing the relative TEC changes, epoch by epoch, along the signal paths from each individual to the receiver, as shown in Equation (1). The index ROTI is defined as the standard deviation of ROT over a 5 min time interval, as shown in Equation (2).  
\[\text{ROT}=\frac{\Delta STEC}{\Delta t} \tag{1}\]  
\[\text{ROTI}=\sqrt{\left\langle\text{ROT}^{2}\right\rangle-\left\langle\text{ ROT}\right\rangle^{2}} \tag{2}\]  
where \(STEC\) represents the TEC along the ray path from the satellite to the receiver (in TECU) and \(\Delta t\) (in seconds) denotes the sampling interval.  
In this study, dual-frequency GPS data are provided by the Crustal Movement Observation Network of China, and 21 continuously operating GNSS tracking stations are selected to detect TEC fluctuations associated with ionospheric disturbances over China, as shown in Figure 1. Dual-frequency GPS observations are sampled at 30 s intervals; the cut-off elevation angle is set at 15\({}^{\circ}\); and the selected time period is from 2002 to 2012, although some data were missing.  
First, original dual-frequency GPS phase and pseudo-range data from the 21 selected sites were preprocessed by removing gross errors and then detecting and repairing cycle slips using Melbourne-Wuebbena linear combinations, geometry-free linear combinations, and ionosphere-free linear combinations (for more details, refer to [40, 41, 42, 43, 44]). Then, we calculated the ROT along the signal paths (epoch by epoch), which allowed us to obtain the corresponding TEC fluctuation index ROTI. Finally, we compared and analyzed the characteristics and regional differences in TEC fluctuations among the 21 GNSS tracking sites.