esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 ITS Standards and Projects
### ITS Research Projects  
As described above, ITS is a multidisciplinary and cross-sectoral research area, which can only be achieved through the convergence and synergy of research on many different research topics. For this reason, research on ITS is typically conducted through large research projects. This section surveys the most important research projects that have been developed in the past and that are currently active. Figure 7: WAVE standards for the ITS communications layered architecture (U.S.). Many ambitious projects have been completed. Some notable examples are: (i) Open vehicular secure platform project (OVERSEE - EU/FP7) [34], which realized an open and standard-compliant in-vehicle platform to enable the development of secure ITS applications and to ensure a high level of isolation between independent applications; (ii) E-safety vehicle intrusion protected applications project (EVITA - EU/FP7) [35], which proposed and developed a secure in-vehicle communication architecture that is robust to thwart tempering and to protect sensitive data inside the vehicle; (iii) Privacy enabled capability in co-operative systems and safety applications project (PRECIOSA - EU/FP7) [36], which analyzed and evaluated privacy-related issues in cooperative vehicular and road safety systems and proposed a privacy aware architecture for V2V and V2I communications; (iv) Intellidrive for safety, mobility, and user fee project (Intellidrive - U.S.) [37], which designed and evaluated new security mechanisms for V2V and V2I communications, which were experimentally evaluated through real deployments; (v) SafeSpot project (EU/FP6) [38], which designed dynamic and cooperative _ad hoc_ networking and localization mechanisms for V2V and V2I communications; (vi) Secure vehicle communication project (SEVECOM - EU/FP6) [39], which proposed security architecture, protocols and mechanisms for vehicular communications systems, including identity management, data consistency and privacy and performance evaluation; and (vii) Cooperative cars and roads for safer and intelligent transportation systems project (CopITS - Qatar National Research Fund) [40], whose objective was to develop advanced communication protocols and networking services to enhance the data transfer over V2V and V2I links and to evaluate them using an ETSI ITS standard-compliant [10] platform and real deployment scenarios. More recently, new research projects have been launched or are ongoing.
###### Abstract  
Consider a collection of entities moving continuously with bounded speed, but otherwise unpredictably, in some low-dimensional space. Two such entities encroach upon one another at a fixed time if their separation is less than some specified threshold. Encroachment, of concern in many settings such as collision avoidance, may be unavoidable. However, the associated difficulties are compounded if there is uncertainty about the precise location of entities, giving rise to potential encroachment and, more generally, potential congestion within the full collection. We adopt a model in which entities can be queried for their current location (at some cost) and the uncertainty region associated with an entity grows in proportion to the time since that entity was last queried. The goal is to maintain low potential congestion, measured in terms of the (dynamic) intersection graph of uncertainty regions, at specified (possibly _all_) times, using the lowest possible query cost. Previous work in the same uncertainty model addressed the problem of minimizing the congestion potential _of point entities_ using location queries of some bounded frequency. It was shown that it is possible to design query schemes that are \(O(1)\)-competitive, in terms of worst-case congestion potential, with other, even clairvoyant query schemes (that exploit knowledge of the trajectories of all entities), subject to the same bound on query frequency. In this paper, we initiate the treatment of a more general problem with the complementary optimization objective: minimizing the _query frequency_, measured as the reciprocal of the minimum time between queries (granularity), while guaranteeing a fixed bound on congestion potential _of entities with positive extent_ at one specified target time. This complementary objective necessitates quite different schemes and analyses. Nevertheless, our results parallel those of the earlier papers, specifically tight competitive bounds on required query frequency.  
Keywords:data in motion; uncertain inputs; collision avoidance; online algorithms; competitive analysis +
Footnote †: This paper is an extended version of our paper published in the International Symposium on Fundamentals of Computation Theory, Tier, Germany, 18-21 September 2023.
# Electrification in Maritime Vessels: Reviewing Storage Solutions and Long-Term Energy Management
## 4 Maritime Battery Projects
### Major Market Players of Energy Storage Systems for Maritime Industry  
The large-scale use of batteries in hybrid and all-electric marine vessels requires professionalism on points of overall vessel performance, reliability, and safety. There are some key players, such as Corvus Energy, Leclanche, and EST-Floattech, leading providers of high-quality energy storage solutions for the maritime industry in Europe. These companies have extensive amounts of experience in the field of marine vessels' storage systems. Corvus Energy has pioneered with more than 750 projects across almost every maritime segment [121,122]. Likewise, EST-Floattech has also supplied more than 200 projects [123]. All mentioned companies produce a scalable and modular rack-type battery module [108,123,124]. The rack-type battery module system requires battery room for  
Figure 11: Demonstration of maritime battery systems’ energy and power according to energy density and C-rate discharge.  
\begin{table}
\begin{tabular}{l l} \hline \hline \multicolumn{1}{c}{**Products/Vessels**} & \multicolumn{1}{c}{**Character**} \\ \hline Mobile phone & High energy, short life \\ Nissan Leaf & High energy, medium life \\ Tesla Model S100d & High energy, medium life \\ Ampere—the first modern electric car ferry & Medium power, long life \\ Aurora and Tycho Brahe—the world’s largest & Medium power, long life \\ electric vessels & \\ \hline \hline \end{tabular}
\end{table}
Table 3: The required features of battery systems as applications [114].  
installation. The rack system consists of Li-ion battery cells and a safe battery management system for a longer system lifetime and high performance. Specifically, Leclanche shares that its cells used in the marine industry are manufactured from high-energy G/NMC and high-power LTO for battery systems. These materials have the advantage of providing high energy and long cycle life. In addition, all companies produce modules available at different heights to enable batteries to fit all battery room sizes according to the vessel type [108; 123; 125].
## 3 Experimental Results
### Horizontal Load-Displacement Hysteretic Curve and Skeleton Curve  
Figure 5 shows the representative hysteretic curves in each group and the standardized skeleton curves for each specimen. The reason for the standardizing skeleton curve is that there are many factors affecting the hysteretic curves, including the axial compression ratio, the aspect ratio, the material properties, etc. If we use the dimensionless coordinates, we can obtain a good regular relationship. In the case of dimensionless analysis, taking into account that the shear wall has no obvious yield point, the limit load point (P\({}_{\text{m}}\), \(\Delta_{\text{m}}\)) is selected as the reference point.  
It can be seen that the hysteretic curves and skeleton curves of the laminated wall and the cast-in-place wall are relatively plump. Before the cracking, the hysteretic curve is basically straight, the area surrounded by the hysteretic loop is approximately zero, and the wall is in the elastic working state. With the increase of displacement, the horizontal load increases, and oblique cracks appear at the lower part of the wall. The cracks can be basically closed when unloading, and the non-linear character is not obvious. As the displacement continues to increase, the number of cracks gradually increases, and the hysteretic loop area gradually expands, with residual deformation after unloading. The hysteretic curve appears to have a good anti-S shape, and the specimen shows good energy dissipation capacity. Compared with the cast-in-place components, the plump part of the hysteretic curve of the laminated wall is similar, and some are even plumper than the cast-in-place components, indicating that the factory can guarantee the quality of the prefabricated components very well. The discussion in the literature [41] also demonstrates similar conclusions. By comparing the structural measures of type I and type II, together with the hysteretic curve and skeleton curve, it can be concluded that the two kinds of construction measures and the joint surface construction technology have little effect on the seismic performance of specimens.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Number** & **Designed Peak Load (kN)** & **Measured Peak Load (kN)** & **Average Peak Load (kN)** & **Ductility Coefficient** \\ \hline PCFI-A1 & & 1003.2 & & 3.46 \\ PCFI-A2 & 774.8 & 1039 & 1046.6 & 3.16 \\ PCFI-A3 & (873.2) & 1097.6 & & 3.15 \\ \hline SWA & & 1053.1 & 1053.1 & 3.45 \\ \hline PCFI-C1 & & 1104 & & 3.63 \\ PCFI-C2 & 777.2 & 1024.9 & 1054.5 & 3.59 \\ PCFI-C3 & (891.6) & 1034.6 & & 3.73 \\ \hline SWC & & 980.3 & 980.3 & 4.52 \\ \hline PCFI-C1 & & 1174 & & 3.43 \\ PCFI-C2 & 777.2 & 1251 & & 3.38 \\ PCFI-C3 & (943.2) & 950 & 1150 & 3.3 \\ PCFI-C4 & & 1225 & & 3.62 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Peak load and ductility coefficient.  
Figure 5: Hysteretic curves (**a–f**) and standardized skeleton curves (**g–i**).
## 1 Introduction
However, phase shifters are subject to strict size constraints in arrays where individual antenna elements must be integrated with phase shifters. [17; 18]. Therefore, we propose a novel approach to improve the phase shifting range of LC-based SIW phase shifters by incorporating inductive posts (IPs) without expanding the device's dimensions. The IPs induce a phase advance that is proportional to the relative permittivity of the substrate (\(\varepsilon_{r,sub}\)) [19], resulting in an enhanced differential phase shift (\(\Delta\phi\)). To validate this concept, we designed and compared structures with and without IPs, and our simulation results demonstrate that the insertion of IPs leads to a greater differential phase shift compared to LC-based SIW phase shifters that rely on additional LCs. Hence, we believe that the integration of IPs can enhance the phase shifting range while maintaining a compact and cost-effective design, making it a promising solution for future telecommunication systems.
# Inversion of a Thunderstorm Cloud Charging Model Based on a 3D Atmospheric Electric Field
## 3 Experimental Results and Analysis  
### Three-Dimensional Atmospheric Electric Field and Radar Observation Experiments  
More than one year of observation experiments were carried out using our three-dimensional atmospheric electric field meter [20]. Figure 4 is a three-dimensional electric field curve for the period from 14:35 p.m. to 17:15 p.m. on 9 October 2018. It can be seen from the figure that the change of the ground electric field caused by the thunderstorm cloud can be divided into four stages. In the first stage (14:35 p.m.-15:25 p.m.), the atmospheric electric field \(E_{z}\) on the ground appeared to fluctuate continuously and the amplitude began to increase. The charge carried by the thunderstorm cloud entered the detection range of the three-dimensional atmospheric electric field meter, but was also far away. In the second stage (15:30 p.m.-15:50 p.m.), due to the discharge phenomenon, the atmospheric electric field \(E_{z}\) oscillated greatly, the polarity was reversed multiple times, and the charging and discharging process was obvious. The thunderstorm cloud is located directly above the observation point. In the third stage (15:50 p.m.-16:25 p.m.), the atmospheric electric field \(E_{z}\) gradually weakens, and the horizontal electric field and electric field amplitude reach a peak multiple times. It was judged that the thunderstorm cloud was located in the east direction of the observation point and the distance was relatively close. In the fourth stage, after 16:25 p.m., \(E_{x}\), \(E_{y}\), and \(E_{z}\) gradually decreased and tended to be stable, and the thunderstorm cloud gradually moved away from the detection range.  
At the same place, the radar map of the same location from 15:06 p.m. to 16:12 p.m. are shown in Figure 5. The central point of the circle was the observation point of the three-dimensional atmospheric electric field meter \(A\). It can be clearly seen that at 15:06 p.m., the thunderstorm cloud was far away from the observation point, and the amplitudes of \(E_{x}\), \(E_{y}\) and \(E_{z}\) were smaller. At 15:30 p.m., the thunderstorm cloud approaches the observation point \(A\) gradually, and the \(E_{z}\) component increases. At 15:48 p.m., the thunderstorm cloud is located directly above the three-dimensional atmospheric electric field meter, and the \(E_{z}\) component measured is strong. At this time, thunderstorm occurrence is predicted. At 16:12 p.m., the thunderstorm cloud over the region moves southeast, still within the detection range, and \(E_{x}\) and \(E_{y}\) increase gradually. The movement of thunderstorm clouds in this period is consistent with that measured by three-dimensional atmospheric electric field meter.  
Figure 4: Three-dimensional atmospheric electric field curve.  
Figure 5: Radar map.
###### Abstract
This study focuses on segmenting MRI modalities using a deep learning approach centered on the U-Net architecture [11] with an attention mechanism suitable for segmenting lesions of different sizes caused by ischemic strokes and capable of rapid training. The remainder of this document is structured as follows: Section 2 reviews the related works, providing context and background on previous research. Section 3 outlines the materials and methods employed in this study, starting with an overview of the proposed approach, including details on the network architecture, loss function, and optimizer. The experimental setup is detailed in Section 3.2, covering the datasets, data augmentation procedure, hyperparameter optimization, and metrics used to evaluate the results. Then, results are presented in Section 4, with subsections dedicated to ablation testing, segmentation results in different MRI modalities, comparisons with state-of-the-art methods, evaluations in the coronal and sagittal planes and performance of the proposed approach on another dataset. Finally, Section 5 discusses the findings, followed by the conclusions in Section 6.
# Hypergraph Analysis of Functional Brain Connectivity During Figurative Attention
## 6 Hypergraph Construction
### Multilayer Hypergraphs  
The hypergraphs of figurative attention can be represented as multilayer hypergraphs, where each layer corresponds to a hypergraph capturing increased or decreased connectivity at a specific frequency. This approach allowed us to consolidate four separate hypergraphs into two four-layer hypergraphs, one for left-cube attention and another one for right-cube attention. The resulting four-layer hypergraphs are presented in Figures 15 and 16.  
As shown in Figure 15, for the left-cube attention, the layers exhibiting increased and decreased connectivity are not interconnected, meaning they do not share common nodes. Notably, the layers associated with increased connectivity at \(f_{1}\) and \(f_{2}\) are primarily linked through the left parietal lobe (P3). Conversely, the layers related to decreased connectivity at \(f_{1}\) and \(f_{2}\) are mainly connected via the central lobe (Cz). These nodes demonstrate the most significant increase and decrease in connectivity, respectively.  
In contrast, Figure 16 reveals that for the right-cube attention, the layers of increased and decreased connectivity are strongly interconnected. Specifically, the layer with in  
Figure 14: Hypergraph \(\mathcal{H}_{4}\) associated with right-cube attention for \(f_{2}\), presented as a bipartite graph (**left**), a Venn diagram (**middle**), and a brain map (**right**). The lower Venn diagram (\(e_{2}\), \(e_{4}\), \(e_{6}\)) indicates deactivation of central-parietal area, while the upper one (\(e_{1}\), \(e_{3}\), \(e_{5}\)) depicts activation of frontal cortex.  
Figure 15: Four-layer hypergraphs representing brain connectivity (**left layers**) and disconnectivity (**right layers**) associated with left-cube attention. The lines indicate inter-layer connections, with the corresponding channels responsible for these links labeled near the lines.  
creased connectivity at \(f_{1}\) is linked through three nodes (FP1, F7, and F8) to the layer of decreased connectivity at \(f_{2}\). Simultaneously, the layer of increased connectivity at \(f_{2}\) is connected via three nodes (Pz, P3, and P4) to the layer of decreased connectivity at \(f_{1}\). This indicates a reciprocal relationship, where an increase in connectivity at \(f_{2}\) is accompanied by a decrease at \(f_{1}\), and vice versa.
## 3 Hardware Architecture of the Proposed STFT Processor  
### Variable Overlap Ratio of the Proposed STFT Processor  
Because a single data stream is input to the STFT processor, we need a windowing module (WM) that receives a single data stream and creates four data streams that overlap by 75% between each channel. For a window length of \(N\), the input and output data flows of the WM are as shown in Figure 5. The output data of channel 1 is delayed by \(3N/4\) cycles of the input data stream, and the output data of channel 2 is delayed by \(N/2\) cycles of the input data stream. The output data of channel 3 is delayed by \(N/4\) cycles of the input data stream. Finally, the output data stream of channel 4 is output without delaying the input data stream. The FFT operation starts after the first data of channel 1 is delayed by \(3N/4\) cycles. That is, the FFT operation starts when the data on channel 1 and channel 2, channel 2 and channel 3, channel 3 and channel 4 overlap by 75% each and are input into the FFT processor.  
As previously stated, it is possible to change the overlap ratio by approximately selecting output channels of the FFT processor. For example, we can obtain 50% overlapped STFT result by selecting output channels along to blue arrow in Figure 6, because channels 1 and 3 overlap by 50%. Similarly, 25% and 75% overlapped STFT results can be obtained along to red and green arrows, respectively. If only channel 1 is selected, we can obtain STFT result of the non-overlapped data streams.  
Figure 4: STFT processor based on a radix-4 multi-path delay commutator (R4 MDC) fast Fourier transform (FFT) processor.  
Figure 5: Input and output data flow of the windowing module (WM).  
Figure 3: STFT processor based on R2 SDF FFT processors.
## 4 Link Budget
### Link Budget under Realistic Atmospheric Conditions
#### 4.2.1 Study Areas  
The link budget is performed on the most important forest types. The tropical and boreal forests are the broadest ones with surface of \(\sim\)2000 \(\times\) 10\({}^{6}\) (10% of land) and \(\sim\)1000 \(\times\) 10\({}^{6}\) ha, respectively (by the Office National des Forets, [71]). From the global land-cover map in 2011 derived from MODIS product MCD12C1 as shown by Figure 13a, we chose two areas of 10 \(\times\) 6 (shown by the black boxes in Figure 13a): one is located in Congo basin (Africa) (1\({}^{\circ}\)N, 20\({}^{\circ}\)E) which represents the tropical forest with the dominant land-cover of evergreen broadleaf forests; the other is located in North-Asia (58\({}^{\circ}\)N, 101\({}^{\circ}\)E), close to the lake Baikal in Russia, which represents boreal forests with mainly mixed forests and a few needleleaf forests. The more accurate land-cover maps derived from MCD12Q1 (MODIS) for the two selected areas (shown in Figure 13b) were used in our model.  
\begin{table}
\begin{tabular}{r r r r r r r} \hline \hline  & **Orbit** & & **CALIPSO** & **ICESat** & **MERLIN** & **ADM-Aeolus** & **ISS** \\ \hline \multicolumn{6}{c}{Orbit altitude \(\tau_{\mathrm{p}}\)(km)} & 705 & 600 & 506 & 400 & 350 \\ Required laser & Forest & Forest area & & & & \\ pulse energy & class & proportion & & & & \\ E (mJ) & \(FOT\) \(\leq\) 1 & 30\% & 333.6 & 241.7 & 171.9 & 107.4 & 82.2 \\ at 355 nm & \(FOT\) \(\leq\) 2 & 75\% & 906.9 & 656.9 & 467.2 & 292 & 223.5 \\  & \(FOT\) \(\leq\) 1 & 30\% & 11.4 & 8.3 & 5.9 & 3.7 & 2.8 \\ E (mJ) & \(FOT\) \(\leq\) 2 & 75\% & 31.0 & 22.5 & 16.0 & 10.0 & 7.7 \\ at 1064 nm & \(FOT\) \(\leq\) 3 & 92\% & 84.4 & 61.1 & 43.5 & 27.2 & 20.8 \\  & \(FOT\) \(\leq\) 4 & 98\% & 229.4 & 166.1 & 118.2 & 73.8 & 56.5 \\ \multicolumn{6}{c}{Example: laser pulse energy E = 100 mJ at the wavelength of 1064 nm} \\ \multicolumn{6}{c}{\(TOT_{\mathrm{max}}\) for good detection} \\ \multicolumn{6}{c}{(\(TOT=FOT/2+\tau\), Equation (4))} \\ \hline \hline \multicolumn{6}{c}{_FOT_: forest optical thickness. _TOT_: total optical thickness. \(\tau\): total atmospheric optical thickness.} \\ \end{tabular}
\end{table}
Table 6: Required energy \(E\) in 355 nm or 1064 nm to get a good detection (GE SNR \(\sim\)10) under ideal atmospheric conditions for 4 forest classes. Each class represents forests with forest optical thicknesses (\(FOT\)) less than a certain value (1, 2, 3, 4). The corresponding area proportion of each forest class among the total forest area is also given. An example of maximum value of the total optical thickness (\(TOT_{max}\)) at which the detection is still good, for a lidar system emitting 100 mJ at 1064 nm, is also given. The instrumental parameters used are given in Table 1.