esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
SLAM (Simultaneous Localization and Mapping), primarily relying on camera or LiDAR (Light Detection and Ranging) sensors, plays a crucial role in robotics for localization and environmental reconstruction. This paper assesses the performance of two leading methods, namely ORB-SLAM3 and SC-LeGO-LOAM, focusing on localization and mapping in both indoor and outdoor environments. The evaluation employs artificial and cost-effective datasets incorporating data from a 3D LiDAR and an RGB-D (color and depth) camera. A practical approach is introduced for calculating ground-truth trajectories and during benchmarking, reconstruction maps based on ground truth are established. To assess the performance, ATE and RPE are utilized to evaluate the accuracy of localization; standard deviation is employed to compare the stability during the localization process for different methods. While both algorithms exhibit satisfactory positioning accuracy, their performance is suboptimal in scenarios with inadequate textures. Furthermore, 3D reconstruction maps established by the two approaches are also provided for direct observation of their differences and the limitations encountered during map construction. Moreover, the research includes a comprehensive comparison of computational performance metrics, encompassing Central Processing Unit (CPU) utilization, memory usage, and an in-depth analysis. This evaluation revealed that Visual SLAM requires more CPU resources than LiDAR SLAM, primarily due to additional data storage requirements, emphasizing the impact of environmental factors on resource requirements. In conclusion, LiDAR SLAM is more suitable for the outdoors due to its comprehensive nature, while Visual SLAM excels indoors, compensating for sparse aspects in LiDAR SLAM. To facilitate further research, a technical guide was also provided for the researchers in related fields.  
3D SLAM; Visual SLAM; LiDAR SLAM; 3D reconstruction; robotics
# Bi-Directional Point Flow Estimation with Multi-Scale Attention for Deformable Lung CT Registration
## 3 The Proposed Approach
### Progressive Flow Refinement
#### 3.4.1 Warping and Cost Volume Construction.  
The estimated flow \(\mathbf{v}^{(l+1)}\) at the coarser level \(l+1\) is propagated to the finer level through inverse distance weighted interpolation, producing an initial flow estimate \(\hat{\mathbf{v}}^{(l)}\) at the resolution \(l\). We use the upsampled flow \(\hat{\mathbf{v}}^{(l)}\) to warp the target points:  
\[\hat{\mathcal{Q}}^{(l)}=\{\mathbf{q}_{i}^{(l)}+\hat{\mathbf{v}}_{i}^{(l)}| \mathbf{q}_{i}^{(l)}\in\mathcal{Q}^{(l)}\},\]  
bringing the target points into approximate alignment with the source. This reduces large residual displacements and stabilizes the subsequent refinement steps.  
Next, we construct a cost volume encoding the local geometric and feature-level differences. For each source point \(\mathbf{p}_{i}^{(l)}\in\mathcal{P}^{(l)}\), we first identify its \(k\)-nearest neighbors among the warped target points \(\hat{\mathcal{Q}}^{(l)}\). Then, leveraging the warped target features \(\mathbf{F}_{\hat{\mathcal{Q}}}^{(l)}\), we compute the residual feature embeddings between the source features \(\mathbf{F}_{\mathcal{P}}^{(l)}\) and their corresponding neighboring warped target features. These residual embeddings are subsequently aggregated via PointConv layers [38], resulting in the cost volume features \(\mathbf{C}^{(l)}\), which effectively encode the geometric proximity and the discrepancies in the local appearance to guide the flow refinement.  
Figure 2: An overview of the progressive flow refinement at level \(l\). The module consists of two main steps: (1) warping and cost volume construction and (2) the \(l\)-th flow estimator with attention-driven refinement. See Section 3.4 for a detailed description of each module.
## 3 Single-Image Destriping Method
### Piecewise Linear Least Squares Fitting for Restoring Details  
Most of the image details can be restored during multi-level iterations, but some linear structures are very similar to stripes, and they cannot be wholly recovered by relying on multi-level iterations, and the number of iterations has a significant impact on processing efficiency. Therefore, we use piecewise linear least squares fitting to restore linear details. We first divide the data (\(I_{adaptMM}\) and \(u_{sum}\)) into \(M\) segments along the track direction, and we can get the data \(I_{adaptMM_{m}}\) (\(0<m<M\)) and the data \(u_{m}\) (\(0<m<M\)), and then perform linear fitting between each column data of \(I_{adaptMM_{m}}\) and each column data of \(u_{m}\), finally to obtain the optimal parameters \(k_{m,j}\) and \(b_{m,j}\) of each segment of data.  
The linear model (17) was constructed and the \(k_{m,j}\) and \(b_{m,j}\) was solved by using the Equation (18):  
\[u_{m,j}(i)=k_{m,j}I_{adaptMM_{m,j}}(i)+b_{m,j}, \tag{17}\]  
\[\min_{k,b}\ \ \|u_{m,j}(i)-k_{m,j}I_{adaptMM_{m,j}}(i)-b_{m,j}\|_{2}^{2}. \tag{18}\]  
where \(j\) is the column number and \(m\) is segment number.  
Finally, we use \(k_{m,j}\) and \(b_{m,j}\) to solve the image after linear fitting. After getting \(I_{poly}\), we calculate the middle value of \(I_{poly}\), \(I_{adaptMM}\) and \(u_{sum}\):  
\[I_{polym,j}=k_{m,j}I_{adaptMM_{m,j}}+b_{m,j}, \tag{19}\]  
\[I_{median}=median(I_{poly},I_{adaptMM},u_{sum}). \tag{20}\]  
Compare \(I_{median}\) and \(u_{sum}\) according to the set threshold \(t_{1}\), \(t_{2}\), and a certain range beyond the threshold value is regarded as image details, and the final \(I_{out}\) is the following formula (21).  
\[I_{out}=\begin{cases}I_{median}&if\ |I_{median}-u_{sum}|>t_{2}\\ (I_{median}+u_{sum})/2&if\ {t_{1}}<=|I_{median}-u_{sum}|<=t_{2}\\ u_{sum}&if\ |I_{median}-u_{sum}|<t_{1}\end{cases}. \tag{21}\]In summary, our destriping steps are shown in Algorithm 1.  
```
Input: Image \(I_{s}\) contaminated by stripes, the parameters \(\rho_{b}\), \(W_{min}\), \(W_{max}\), \(W\), \(\lambda_{1}\), \(\lambda_{2}\), \(\alpha\), \(\beta\), out-iter, in-iter, \(t_{1}\), \(t_{2}\)
1: Substitute \(I_{s}\) into Equations (1) to (5). \[I_{\text{adaptMM}}=\textit{adaptMM}(I_{s})\]
2: Initialize \(u_{0}=I_{\textit{adaptMM}}\), \(d_{lx}=d_{ly}=b_{lx}=b_{ly}=0\)
3:for\(n=1\): out-iterdo if(\(n=1\)) then \(f=I_{\textit{adaptMM}}\), \(u_{sum}=0\) else \(f=I_{\textit{adaptMM}}-u_{n}\) endif for\(m=1\): in-iterdo  Compute \({u_{n}}^{m+1}\) by solving (9).  Update \(d_{lx}\) and \(d_{ly}\) by (11) and (14), respectively.  Update the Bregman variable \(b_{lx}\), \(b_{ly}\) by (16). endfor  Update \(u_{sum}\) by \(u_{sum}\) + \(=u_{n}\) endfor
```  
**Algorithm 1**
# The EU Directive on Electromagnetic Fields--Practical Experience of Field Measurements
## 1 Introduction  
The EU directive on minimum health and safety requirements for the exposure of workers to the risks arising from an electromagnetic field (EMF) was adopted as a minimum requirement in June 2013 and introduced in the EU countries in 2016. Still today, many companies are not aware of the legislation and have not taken measures to comply. This could perhaps be due to some of the practical problems they are facing in trying to comply.  
In 2009, [PERSON] et al. [1] wrote a paper on still-open questions and it reviewed some of the problem experienced by this group of authors with expertise in occupational exposure to the EMF. Some of these questions are still of concern and we will here address some of them.  
First, the directive only addresses short-term effects and does not concern possible long-term effects or the possible carcinogenic effects, but it is intended to cover all known direct biophysical effects and other indirect effects caused by EMF exposure.  
Risks assessment of EMF at the workplace should be performed according to the framework directive [2]. Here it is stated that if relevant action levels are exceeded and relevant exposure limit values may be exceeded, an action plan must be implemented to show compliance.  
Special attention shall be paid to workers at risks (pregnant, living with implanted medical devices), including individual risk assessment where applicable.  
When measurements are needed to show compliance, there are several aspects that need to be considered, many of which are not clearly stated in the legislation. Here, some of these issues are discussed.
## 1 Introduction
Based on the above analysis, this paper aimed to exploit high-rate multi-GNSS observations to improve the precision of displacement estimates, especially in the case of BDS. The equations describing the relationship between phase residuals on different frequencies were rigorously derived and validated. The characteristics of BDS residuals were investigated in detail to identify potential problems that could hinder the precision and reliability of the BDS-only PPP. Afterward, the multipath corrections were calculated using the SF approach based on the phase residuals for each satellite. Then, the performance of multi-GNSS UCUD PPP augmented by the SF approach, especially of the BDS-only PPP, was assessed using Jiuzhaigou earthquake data. The rest of the paper is organized as follows. The description of the multi-GNSS PPP data processing strategy is given first in Section 2. Afterward, the equations that describe the relationship between phase residuals on different frequencies are derived. Section 3 presents the multi-GNSS data description. Section 4 displays the analysis of the characteristics of BDS geostationary Earth orbit (GEO) phase residuals, PPP solutions using sidereally filtered multi-GNSS data, especially BDS PPP solutions, and a case study on the Jiuzhaigou earthquake. Finally, in Section 5, the conclusions and perspectives are provided.
# Onboard Centralized ISL-Building Planning for LEO Satellite Constellation Networks
## 1 Introduction
### Contributions  
In this paper, we propose a centralized ISL-building planning scheme to address the problems identified in the previous works and the practical issues encountered in the development of current satellite constellation projects. The Walker Delta constellation is frequently used for LEO large-scale satellite constellation projects with ISLs [5; 25; 26; 27], where ISLs among intra-plane satellites can be built continually. As a result, we focus on the building planning of inter-plane ISLs. This paper's significant contributions are as follows:  
* For the first time, we provide an onboard centralized ISL-building planning scheme that enables efficient ISL-building planning onboard the satellite and decouples the entire planning process from ground station control;
* We take into account that a satellite has multiple antenna terminals that can simultaneously participate in the ISL building. Furthermore, in order to approach the visibility calculation as closely as possible in the engineering implementation, we consider the impact of the terminal's installation direction, the turntable's rotation angle threshold, and the satellite's attitudes on inter-plane visibility;
* In order to address the problem of the high computational complexity of ILP, we propose a link-building planning method based on topology stability optimization for inter-plane ISLs. This method can be applied to situations in which satellite onboard computing resources are severely limited;
* The ISL-building planning scheme proposed in this paper was evaluated through experimental simulation and compared with the current commonly used methods. Through the analysis of the results, it is found that the method can achieve positive results in performance indicators such as ISL switching frequency, topology stability, average delay, and maximum delay.  
The remainder of this paper is organized as follows. The onboard centralized ISL-building planning scheme is described in Section 2. Sections 3 and 4 cover the ISL-building planning scheme's two key processes: visibility computation and inter-plane link building planning. Section 5 describes the experimental simulation of the ISL-building planning method proposed in this paper, and provides the analysis and evaluations of the results. Section 6 summarizes the paper.
Recently, carbon-based electrodes such as activated carbon (AC), carbon nanoparticles, carbon nanotubes, and graphene-based nanosheets have been widely studied. These can improve the specific surface area of a CF electrode and catalyze the redox reaction, but its resistance will be higher. So, the combination of carbon-based materials with metal elements has been studied in order to effectively catalyze the vanadium redox couples. For example, platinum with high electric conductivity and stability was mixed with carbon black and graphene. [PERSON] et al. [32; 33; 34] investigated the reaction rate of VRFBs by PT/C (Vulcan XC-72). It was reported that the Co-based metal-organic framework (Co-MOF) ZIF-67 was a perfect carbon material for lithium batteries due to its porous structure. [PERSON] et al. [35] reported on a GF electrode that was pasted with CoP that could effectively promote the V(IV)/V(V) redox reaction, and the CoP power was synthesized by direct carbonization of ZIF-67. ZIF-67 is a Co-based metal-organic framework (MOF) consisting of metal ions or clusters coordinated with organic ligands to form one-, two-, or three=dimensional structures. MOFs are a subclass of coordination polymers with porous features. Due to their special structure and metallic characteristics, MOFs are used in gas purification, gas separation, and catalysis, and as sensors and supercapacitors [36; 37]. In this paper, a novel type of metal-carbon composite on CF was prepared, and it contributed to the performance improvement of VRFBs. Firstly, ZIF-67 was grown in situ on CF as a precursor, in a new attempt to replace the traditional postbonding process. Then, the ZIF-67@CF was treated in a vacuum oven with inert gas, and a cobalt mixed nitrogen 3D carbon nanostructure with carbon felt (Co-CN@CF) was prepared. With this method, the as-prepared Co-CN particles on the CF maintained the morphology of ZIF-67, which is a regular dodecahedron. The Co-CN@CF was used as a novel catalyst in a VRFB to increase the specific surface area and improve the electrochemical catalysis capability of CF. The results showed that the Co-CN@CF exhibited excellent electrochemical activity toward VO\({}^{2+}\)/VO\({}_{2}\)\({}^{+}\) redox couples in the VRFB, with an average cell voltage efficiency (VE) of 86% and an energy efficiency (EE) of 82% at 80 mA cm\({}^{-2}\), which was increased by more than 10% compared with the traditional carbon felt.
# Tsunami Modeling and Satellite-Based Emergency Mapping: Workflow Integration Opportunities
## 2 Materials and Methods: Tsunami Modelling and Satellite-Based Emergency Mapping
### Early Tasking Approaches Based on the Tsunami Model Output
#### 3.3.1 Maximum Wave Height and Populated Place Categories  
The tsunami model estimates the maximum wave height impacting on a set of locations distributed along the coast. By simply dividing the estimated maximum wave height with the city class (which can be considered a proxy of the population) in the range from 1 to 6 (the classes used by Europa Technologies Global Insight Plus dataset, where value 1 indicates that the place is a capital, 2 is a major city running down to 6 which indicates a village or other minor settlement: [[https://www.europa.uk.com/map-data/global-map-data/global-insight/global-insight-faq/](https://www.europa.uk.com/map-data/global-map-data/global-insight/global-insight-faq/)]([https://www.europa.uk.com/map-data/global-map-data/global-insight/global-insight-faq/](https://www.europa.uk.com/map-data/global-map-data/global-insight/global-insight-faq/))) it is possible to obtain an index that takes into consideration the exposure (expressed as importance of the location) where higher values represent locations more at risk. Classifying such index in 3 classes based on the [PERSON] natural breaks classification method [5] and then grouping together adjacent pixels in the same class, 3 areas of interest with higher priority and other 5 with lower priority (Figure 12a) are identified. With the proposed approach, one of the most affected areas, La Serena and Coquimbo, were not identified, due to both the latitudinal shift of the estimated maximum wave height compared to the measured one (as shown in Figure 6, leading to values lower than 1 m in such areas) and the relatively low importance in terms of inhabited location class (both are in city class 3).  
The main drawback of a similar approach is related to the heterogeneous accuracy, incompleteness and level of update of the populated places categories.
# A Comprehensive Review on Network Protocol Design for Autonomic Internet of Things
## 3 Review of Protocol Designs
### Protocol Designs for MAC Layer
#### 3.1.3 [PERSON] et al. in [12] proposed the Receiver Initiated Energy Harvesting MAC (ERI-MAC) protocol for multi-hop energy harvesting WSNs. This protocol implements merger scheme and queuing model of data packets to adjust the duty cycle on a node in order to achieve the ENO condition. The ERI-MAC's strategy of data sending is similar to OD-MAC's. When a node is in a wake up state and there is no data packet, which is scheduled to be sent, the node will transmit a beacon packet containing its ID to declare its readiness to accept data delivery of forwarding. When a waiting sender receives the beacon, the data packet is sent to the queue system by a First In First Out (FIFO) fashion. An acknowledgment packet will be sent to confirm that the entire data packet has been received successfully, which will also serve as the beacon for the next delivery readiness.  
To achieve the ENO condition, ERI-MAC makes packet queue so that each queue has a duration that is safe to ensure the maximum energy consumed is equal to the energy gained from the energy harvesting activity. The ratio of energy consumed to energy gained is calculated periodically.  
The ERI-MAC protocol has been validated by simulation. As the result, it can be proved that the network nodes can adjust the data transmission activity to the level of the energy harvesting. The ERI-MAC weakness is when the level of energy harvesting is very low, the data transmission activity that combines multiple packets may cause the duration of time that is no longer safe. For example the energy consumption is likely to be greater than the energy gained from the energy harvesting activity.
# Research on Tracking Technique Based on BPSK-CSK Signals
## 3 Results
### Verification Results
During the signal convergence process, the method in this paper is able to track signal changes stably and maintain high demodulation accuracy. This means that in the case of poor signal quality or interference, the method in this paper can still effectively extract useful information and ensure the reliability and stability of communication.
## 3 Technical Preliminaries
### Notations and Cryptographic Functions  
Table 1 explains the notations and main cryptographic functions used in the proposed protocol.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Notation** & **Description** \\ \hline \(S_{m}\) & \(m^{th}\) server \\ \(P_{i}\) & \(i^{th}\) patient \\ \(prk_{m},puk_{m}\) & Private key, public key of \(S_{m}\) \\ \(Cert_{m}\) & Certificate of \(S_{m}\) \\ \(\delta_{m,j}\) & Signature of \(P_{i}\)’s message signed by \(S_{m}\) \\ \(G_{(x,y)}\) & Basic point on the curve \(Ep(a,b)\) \\ \(ID_{i}\) & Identity of \(P_{i}\) \\ \(PW_{i}\) & Password of \(P_{i}\) \\ \(B_{i}\) & Biometrics of \(P_{i}\) \\ \(T\) & Timestamp \\ \(||\) & Concatenation operation \\ \(\oplus\) & Exclusive-or (XOR) operation \\ \(h(.),h_{bio}(.)\) & One-way hash function, biohash function \\ \(E_{k}(.),D_{k}(.)\) & Symmetric encryption, decryption algorithms using key \(k\) \\ \([.]_{SC_{i}}\) & Storage parameters in \(P_{i}^{\prime}\)’s smart card \\ \([.]_{MD_{i}}\) & Storage parameters in \(P_{i}^{\prime}\)’s mobile device \\ \hline \hline \end{tabular}
\end{table}
Table 1: Notations and cryptographic functions used in the paper.
## 6 Evaluation
### Performance Evaluation  
Our performance evaluation was conducted through two scenarios: (i) cost-effectiveness and (ii) the system's scalability and throughput under different operational loads. For this evaluation, we used a machine with an Intel i5-8250U processor with 6 GB RAM.
## 5 Conclusions  
This paper presents a correlation-based AIM under wider frequency trip settings for DG. Since a significant loss of DG due to a short disturbance could cause another reliability issue for an EPS, wider frequency trip settings were introduced in IEEE Std. 1547-2018. Under these conditions, the conventional AIM might not detect islanding with lower current distortion. Thus, the proposed method presents an islanding detection indicator as the correlation parameter between current disturbance and the corresponding frequency, and shows high islanding-detection capability with less current distortion through simulation results. According to the simulation results, the proposed AIM method detects islanding under the IEEE Std. 1547-2018 test condition within 2 s, which meets the standard requirement, and it has around 3.18% _THDi_, which is relatively lower compared with the conventional AFD method having 5% _of_.  
**Funding:** This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) [grant number 2019R1H1A1080039].  
**Conflicts of Interest:** The authors declare no conflicts of interest.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \begin{tabular}{c} **AIM** \\ **Parameter** \\ \end{tabular} & \multicolumn{3}{c}{\begin{tabular}{c} **AFD Method** \\ **(Fixed _cf_)** \\ \end{tabular} } & \multicolumn{3}{c}{\begin{tabular}{c} **AFDPF Method** \\ **(Varying _cf_)** \\ \end{tabular} } & \multicolumn{3}{c}{\begin{tabular}{c} **The Proposed Method** \\ **(Varying _cf_)** \\ \end{tabular} } \\ \hline _cf_ [\%] & 1 & 2 & 3 & 4 & 5 & \(cf[k]=cf[k-1]+K_{p}(Freq[k]-Freq[k-1])\) \\ \hline _K\({}_{p}\)_ & \multicolumn{3}{c}{- (No need)} & \multicolumn{3}{c}{0.02} & 0.02 \\ \hline \
\begin{tabular}{c} Anti-islanding \\ detection time [s] \\ at \(\Delta P\) and \(\Delta Q\approx 0\) \\ \end{tabular} & \multicolumn{3}{c}{No detection} & \multicolumn{3}{c}{No detection} & 0.116 \\ \hline
\begin{tabular}{c} \(THD_{i}\) [\%] \\ before islanding \\ \end{tabular} & 3.18 & 3.19 & 3.53 & 4.10 & 5.53 & 3.18 & 3.18 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Performance comparison among AIMs.  
Figure 10: Anti-islanding test results when the proposed method is used.