esa-sceva/satcom-chunk-collection huggingface dataset:
# An Automatic Navigation System for Unmanned Surface Vehicles in Realistic Sea Environments
## 2 The Overview of Unmanned Surface Vehicle System  
The overall structure of the USV system has been systematically described in Figure 1, which illustrates the system with its three major subsystems (the state awareness system, executive system, and autonomous navigation system (ANS)) and the information flow between them. In the paper, the Lanxin USV, which is a small intelligence equipment platform of Dalian Maritime University [30], is used as the research object. The USV is a pod propulsion vessel, so its executive system command is composed of thruster speed and propulsion angle. The environmental information is divided into static information and dynamic information. The static environmental information can be obtained by electronic charts or satellite images. The surrounding dynamic information mainly comes from state awareness systems through on-board equipment (global positioning system (GPS), radars, cameras, and sonar) and the sharing of information with other vessels using radio, automatic identification system (AIS), and network communication. The two kinds of information are applied to global path planning and local path re-planning, respectively.  
Figure 1: The overall structure of the unmanned surface vehicle (USV) system. DTFMS: dynamic domain tunable fast marching square; FCS-MPC: finite control set model predictive control; GPS: global positioning system; AIS: automatic identification system.  
As observed from the USV system structure, the autonomous navigation system plays an important role as it connects both the state awareness system and the execution system. It contains two components, i.e., the PPS and CAS. The PPS can model the static and dynamic environment and generate optimized reference path points by path planning and re-planning and provide them to the CAS. The CAS generates control commands to the executive system that enables the USV to follow the reference path points and complete the local dynamic obstacle avoidance. Meanwhile, the predicted movement information of the USV from the CAS can provide reference for path re-planning. Detailed descriptions of the ANS are given in Sections 3-5. In order to realize the autonomous navigation of the USV, we make following assumptions:  
* The state information of the obstacle is known exactly.
* We have real-time detection of the USV's position, heading, and velocity.
* Global information comes from the electronic chart.
* The mathematical model of the USV can be used to predict future trajectories to evaluate the effect of control commands.  
The proposed structure implies that collision avoidance and control functionality are integrated together. This leads to a more concise structure whereby the controller can directly implement the collision avoidance function, and reliability and safety can be ensured by the structure.
## 3 Results and Discussion
### ECG Delineation
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**AFL Records** & **Class** & **Accuracy** & **Sensitivity** & **Specificity** & **Precision** & **F1** \\ \hline \multirow{3}{*}{35} & **P-wave** & 92.3 & **0** & 92.3 & **0** & **0** \\ \cline{2-7}  & QRS-complex & 95.1 & 83 & 98.9 & 96.1 & 89.1 \\ \cline{2-7}  & T-wave & 80.7 & 36.2 & 99.8 & 98.8 & 53 \\ \hline \multirow{3}{*}{52} & **P-wave** & 96.9 & **0** & 96.9 & **0** & **0** \\ \cline{2-7}  & QRS-complex & 97.3 & 79.4 & 99.7 & 97.3 & 87.4 \\ \cline{2-7}  & T-wave & 90.5 & 72.8 & 94.2 & 71.8 & 72.3 \\ \hline \multirow{3}{*}{103} & **P-wave** & 86.2 & **0** & 86.2 & **0** & **0** \\ \cline{2-7}  & QRS-complex & 96.9 & 91 & 97.9 & 87.8 & 89.4 \\ \cline{2-7}  & T-wave & 85.6 & 49.6 & 95.1 & 72.6 & 58.9 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: The experimental results of AFL detection with iCOR. In recent years, there have been previous studies that provide end-to-end learning for ECG morphology classification (refer to Table 6). [PERSON] et al. [21] proposed the denoising autoencoder (DAE) for denoising algorithms and convolutional-bidirectional long short-term memory (ConvBiLSTM) for ECG delineation to classify ECG waveforms in terms of the P-QRS-T-wave. The denoising reconstruction using unsupervised learning based on the encoder-decoder process can be proposed to improve the drawbacks. First, the ECG signals are reduced to a low-dimensional vector in the encoder. Second, the decoder reconstructs the signals. Finally, the reconstructed signals of ECG can be processed by ConvBiLSTM. The results achieved an accuracy of 99.81%, 99.86%, and 99.35% for P-wave, QRS-complex, and T-wave, respectively. Though the performance results are outstanding, they only concern the normal sinus records for generating the ConvBiLSTM model. [PERSON] et al. [40] conducted experiments on a large-scale 12-lead ECG dataset, ICDIRS, using a variational encoder-decoder network, ECGVEDNET, specifically designed to address morphological variations in ECG signals. In ECGVEDNET, a well-regularized latent space is created, where the latent ECG features adhere to a regular distribution, exhibiting reduced morphology variations compared to the raw data. Additionally, a transfer learning framework is introduced to leverage the knowledge gained from ICDIRS and apply it to smaller datasets. On ICDIRS, ECGVEDNET achieves accuracies of 86.28% for QRS onset and 89.94% for T peak. From the previous studies, it can be claimed that iCOR performs excellently in classifying three primary ECG waveforms, i.e., P-wave, QRS-complex and T-wave. iCOR outperformed the accuracy of P-wave, QRS-complex and T-wave in the previous studies [21; 40]. The performance results of this experiment study look promising, however, there are limitations of this study:  
* This study was only concerned with BW noise for the ECG denoising process using an MLF;
* The testing of iCOR was only explored in noisy ECG signals.
# Performance of a Closed Cycle Power Takeoff for a Shore-Based Wave Energy Device
## 4 Discussion  
In this paper, the complete process of designing a turbine suitable for the closed cycle power takeoff of an oscillating water column device in a shore-based installation has been presented using the breakwater at Mutriku as a case study. Multiple tools were used, from a reduced order model of the entire system to an elementary 1D theory of axial flow turbine and 3D CFD simulations of the blades. The combination of different levels of study with consistent outputs strengthened the authors' confidence in the suitability and performance of the designed turbine. In particular, the assumption of representing the turbine as an orifice in the reduced order system model agrees with the 3D CFD study, with a consistent turbine size metric.  
The total energy captured over the month was 1544 kWh, yielding an average power of 2 kW. Most of this is obtained from sea conditions presenting less than 5 kW at the turbine (see Figures 4 and 5). Thus, in principle, a suitably sized generator could be operated at a capacity factor of approximately 40% since the CCPTO smooths the variability in the pressure at the turbine. It is worth noting that the sea chamber at Mutriku was designed for an open cycle, self-rectifying turbine. A smaller sea chamber volume would increase the maximum pressure achieved and thus increase the average power production but would not change the capacity factor significantly.  
The process followed in this paper to design a turbine suitable for the breakwater at Mutriku is the basis for an optimisation strategy that could be applied to any fixed oscillating water column structure. It is a crucial step in the development of the closed cycle power takeoff in that it shows that the turbine is not a technological obstacle for this type of device. Future work will focus on the detailed design of the other system elements, such as the valves and the chambers, and, in the case of installations such as Mutriku, could consider the pressurization of the high-pressure chamber from multiple sea chambers.  
Conceptualization, C.M.; methodology, M.B. and L.G.; formal analysis, M.B. and L.G.; data curation, M.B. and L.G.; writing--original draft preparation, M.B.; writing--review and editing, C.M. and M.B.; project administration, C.M.; funding acquisition, C.M. All authors have read and agreed to the published version of the manuscript.  
This research was funded by Sustainable Energy Authority of Ireland grant number SEAI/RDD/495.  
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to some of them being proprietary.  
Figure 19: Energy generated by the turbine in April in Mutriku (kWh).
## 5 Case Study
### Analysis of Optimization Scheduling Indicators for Different Types of Pumped Storage
#### 5.3.4 Analysis of Costs under Different Pumped Storage Configuration Schemes  
Table 5 lists the operational cost indicators under different pumped storage configuration schemes. It is evident that from configuration schemes 1 to 8, both thermal power operation cost and total system cost show a downward trend. Among them, the operational cost indicators of scheme 8 are the smallest, and the operational cost indicators of scheme 1 are the largest. Specifically, without pumped storage, the total cost of the system reaches CNY 757,500. Equipped with only FS-PSUs, the cost drops to CNY 78,200. Equipped with only VS-PSUs, the cost further drops to CNY 64,600. Equipped with only T-PSUs, the costs are minimized to CNY 26,500. As indicated in Figures 8 and 9, the increased flexibility of pumped storage plants leads to a reduction in both wind power curtailment rate and thermal power electricity.
# A Novel Self-Forming Virtual Sub-Nets Based Cross-Layer MAC Protocol for Multihop Tactical Network
## 3 Proposed VSCL-MAC Architecture
### Sub-Nets Formation for Simultaneous Data Transmission  
The proposed protocol allows SDRs of the tactical network to be confined into multiple virtual sub-nets. These sub-nets are formed autonomously using entries of TRANS_table, which is similar at every radio; thus, it results in the same sub-nets structure and number. The transmission pattern of nodes shapes sub-nets' structures and has a maximum diameter equal to the network's total number of nodes. Each SDR looks its TRANS_table up and forms virtual sub-nets based on the following rules:  
1. The transmitter MAC ID is equal to the receiver MAC ID of the other entry.
2. The receiver MAC ID is equal to the transmitter MAC ID of the other entry.  
In the case of either rule, SDR belongs to the same sub-net and selects the data channel accordingly. After sub-nets formation, the proposed design uses the FDMA technique that assigns different frequencies to different nodes. The selection of frequency for data transmission is adhesive with the pattern of sub-nets formation. Each node selects a frequency \(f_{h}\) autonomously from a frequency band of range 0 to \(f_{h-1}\) and matches with the lowest ID of the sub-net members. There is no collision in frequency selection among sub-nets because each sub-net has a different lowest node ID, e.g., in Figure 5, sub-net 1 has node4, sub-net 2 has node2, and sub-net 3 has node1 as the lowest member ID of the sub-nets; therefore, use frequency \(f_{4}\), \(f_{2}\), and \(f_{1}\) for data transmission, respectively. The control packets use one frequency from the same range, which is common and time-slotted.  
This virtual confinement of nodes makes the network efficient in resource distribution in a dynamic multichannel network environment. In tactical communication, SDRs use adaptive frequency hopping techniques in which radios continuously hop over multiple frequencies; those techniques are out of this paper's scope. It provides transmission security in jamming and other transmission attacks [30,31].
# Scalable and Reliable Data Center Networks by Combining Source Routing and Automatic Labelling
## 3 The eTorii DCN
### Flexibility: Generalization to Any Hierarchical DCN  
DCNs are usually deployed based on some kind of hierarchy (well-known examples include VL2 [3] or BCube [6]), and routing solutions are many times designed based on these specific topologies. For example, Torii was initially developed to be applied in the fat-tree defined by PortLand [2]. For that reason, one of the main objectives of eTorii was to expand the features of Torii to apply them in any hierarchical topology. GA3 is the cornerstone to accomplish this goal, as described in Section 3.1 and, accordingly, unicast forwarding and path repair in eTorii can be flexibly applied in any type of hierarchical topology, even non-symmetrical, as illustrated in Sections 3.2 and 3.3.  
This approach is very flexible to guarantee, for instance, that routing still works when the DCN is being updated or some part of it fails, as a non-symmetrical topology could also represent a transient state in which the data center is deploying new hardware, progressively. In fact, thanks to GA3, eTorii is even capable of recognising some types of connections, which are usually considered very irregular or even faulty in DCNs, namely: peer-links (links that connect network devices in the same hierarchy level) and cross-links (links between non-adjacent hierarchy levels). This links could be ignored or could directly raise a notification if found and non desired. For example, the topology previously used to illustrate routing and path repair in Figures 2-4 contains a cross-link, as S1 and S9 are directly connected, skipping the intermediate level (comprised of S3, S4, S5 and S6). In this example, the cross-link is used in the routing scheme.
# Mean Reattachment Length of Roof Separation Bubbles Using Proper Orthogonal Decomposition
## 4 Results
### Evaluation of the Mean Attachment Length (\(X_{r}\)) Using the POD Eigenmode  
Among the dominant POD eigenmodes previously analyzed, as observed in Figures 9 and 10, only the first POD eigenmode clearly exhibits the general characteristic patterns of flow separation and reattachment phenomena. Although the first mode contributes only 14% to the total fluctuating wind pressure energy, as shown in Table 1, this value is considered substantial, given the complexity of the fluctuating wind pressures. Based on these observations, the first POD eigenmode was identified as the mode that most significantly contributed to the roof separation and reattachment phenomena.  
The position of mean reattachment, which serves as the boundary between flow separation and reattachment, was determined using the first eigenmode of the POD. Specifically, the contour line with a POD eigenmode value of zero, following the contour line corresponding to the maximum value of the first POD eigenmode, was chosen to represent the mean reattachment location. In this context, the mean reattachment length (\(X_{r}\)) is defined as the distance from the leading edge of the roof, where flow separation begins, to the contour line where the POD eigenmode value is zero, as illustrated in Figure 11.  
Figure 10: The POD eigenmodes, \(\alpha=5^{\circ}\), \(l_{u}=12.7\%\): (a) Mode 1; (b) Mode 2; (c) Mode 3.  
The mean reattachment lengths (\(X_{r}\)) for the intermediate (\(I_{u}=12.7\%\)) and low turbulence intensities (\(I_{u}=0.6\%\)), with a wind angle (\(\alpha\)) of \(0^{\circ}\), were determined by identifying the contour line where the first POD eigenmode value is 0, as illustrated in Figure 11.  
Table 2 presents the assessed maximum, minimum, and average mean reattachment lengths (\(X_{r}\)) across the roof, derived from the first POD eigenmodes under the two flow conditions.  
An evaluation of the mean reattachment lengths (\(X_{r}\)) using the first POD eigenmodes reveals significant variations as the turbulence intensity (\(I_{u}\)) varies from 12.7% to 0.6%. Specifically, the maximum mean reattachment length (\(X_{r}\)) increases approximately 1.7 times, the minimum mean reattachment length (\(X_{r}\)) increases about 2.2 times, and the average mean reattachment length (\(X_{r}\)) undergoes a growth of approximately 2.1 times. These findings emphasize the influence of turbulence intensity (\(I_{u}\)) on reattachment phenomena, as documented in numerous previous related studies [3; 17; 46; 47].
# Enhancing the Photocatalytic Activity of Immobilized TiO2 Using Laser-Micropatterned Surfaces
## 2 Materials and Methods
### Synthesis of Photocatalysts and Coating of Substrates  
Thin TiO\({}_{2}\) films were developed by the sol-gel process, followed by spin-coating on two distinct substrates: flat and microstructured silicon. Glass substrates were also used for UV-visible spectroscopy. Two precursor solutions, labeled A and B, were prepared. Solution A was formulated by dissolving 1 mL of TTIP in 5 mL of C\({}_{3}\)H\({}_{8}\)O\({}_{2}\), while solution B was created by adding 0.15 mL of nitric acid to 0.25 mL of water. The final solution was prepared by carefully adding solution B drop by drop, under stirring, into solution A at 80 \({}^{\circ}\)C. The resultant solution underwent stirring at 80 \({}^{\circ}\)C for 2 h and was subsequently allowed to rest at room temperature (RT) for 1 day. The reference TiO\({}_{2}\) solution, doped with Degussa P25, was prepared by introducing 50 mg of Degussa P25 into 1 mL of the aged TiO\({}_{2}\) solution. Thin films were produced by depositing 6-7 droplets of the final solutions onto different substrates and spin-coating (Laurell WS-400 BX-6 NPP/LITE, Lansdale, PA, USA) at 1400 rpm for 30 s, followed by 400 rpm for an additional 30 s. This spin-coating procedure was repeated three times. Each spin-cast layer was subjected to heating at 100 \({}^{\circ}\)C on a hot plate for 5 min before applying the next layer. Finally, the films underwent thermal treatment at 500 \({}^{\circ}\)C for 3 h in a furnace (MUFFILE FURNACE N-8 L 1100 \({}^{\circ}\)C, JP Selecta, Barcelona, Spain) to achieve the desired crystalline structure [50]. The ramp rate during this thermal treatment was maintained at 2 \({}^{\circ}\)C min\({}^{-1}\). Subsequently, all samples were allowed to cool down to RT.
## 2 Related Work
### NeRF-Based SLAM  
Leveraging the advantages of NeRF, numerous SLAM systems have been developed. IMAP [35] is the first real-time SLAM system to use a continually trained MLP as the sole scene representation for a handheld RGB-D camera. It achieves efficient 3D mapping and tracking through keyframe and multiprocessing innovations. Its emergence has spurred the development of many NeRF-based SLAM systems. NICE-SLAM [36] leverages geometric priors to handle local information, enhancing the system's scalability and robustness for superior performance in large-scale scenes. Co-SLAM [37] combines a multi-resolution hash-grid with one-blob encoding, enabling rapid convergence and surface hole filling for a more robust SLAM performance. Point-SLAM [38] introduces neural anchor points to represent scenes, allowing for a dynamic adjustment of point density based on input image information. This approach reduces optimization time and lowers memory usage in less detailed regions. Although these methods optimize NeRF-based SLAM from various angles, they remain constrained by NeRF's implicit representation and ray-based rendering approach. This limitation hinders a more intuitive optimization of SLAM.
# Exploring the Potential of Event Camera Imaging for Advancing Remote Pupil-Tracking Techniques
## 5 Conclusions  
In conclusion, our proposed event-camera-based pupil-tracking algorithm demonstrated promising results in accurately tracking pupils during rapid eye movements, with real-time capabilities. Specifically, our method reached a detection accuracy rate of 98.1% and a tracking accuracy, where the pupil difference was less than 10 mm, at 80.9%. However, there are challenges to overcome, particularly in handling subtle movements and occluded eye shapes. Future research could focus on expanding the dataset for training and investigating new machine learning techniques to improve the algorithm's performance across diverse eye movement scenarios and lighting conditions. By addressing these challenges, event-camera-based pupil tracking holds great potential for advancing eye-tracking technologies and enabling new applications in various real-world settings.  
Conceptualization, D.K. and J.J.; methodology, D.K. and Y.K.L.; software, D.K.; validation, D.K. and Y.K.L.; formal analysis, J.J.; investigation, Y.K.L.; resources, D.K.; data curation, J.J.; writing--original draft preparation, D.K.; writing--review and editing, Y.K.L. and J.J.; visualization, Y.K.L.; supervision, J.J.; project administration, D.K.; funding acquisition, D.K. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2022R1F1A1074056); this work was supported by the 2023 Hongik University Research Fund. This work was supported by the Ministry of Education (MOE) and a Korea Institute for Advancement of Technology (KIAT) grant funded by the Korea Government (MOTIE) (P0022165, High-Speed Semiconductor IC Design and Test/Signal Integrity Professional Training Project).  
Not applicable.  
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.  
Not applicable.  
The authors declare no conflict of interest.
# BVLOS Unmanned Aircraft Operations in Forest Environments
## 5 Taking a Risk-Based Approach to BVLOS Operations in Forest Environments
### Operational Considerations
#### 5.2.2 Use of Restricted Airspace (or Other Segregated Airspace)  
A simple means of removing airborne risks associated with BVLOS flight is to fly in airspace that does not contain other aircraft [20]. Most commonly, this would be Restricted Airspace (RA) but could be other segregated airspace, such as Military Operating Areas (MOA). As noted earlier, forestry companies can apply to have the airspace above their estate (up to a certain level) made into Restricted Airspace (either temporary or permanent in nature) such that they can control whether other aircraft can enter that airspace or not [20]. Countries do vary on their likelihood of giving this airspace and how easy it is to apply for it. However, the general consideration is whether the imposition of Restricted Airspace would disrupt extant aviation operations [20]. Given that forested areas are typically remote, this approach may make sense for larger estates to avoid the need to purchase sophisticated DAA tools for the aircraft.