esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Local Railway Level Crossing Case Study
### Hazard Identification and Analysis of the Causes  
The hazard identification process aims to highlight all events that could result in harmful consequences for system users. At level crossings (LCs), the main hazardous condition has been identified as the 'Hazardous crossing of the LC' event. This occurs when a train approaches the LC, and due to a failure in one or more systems, the crossing cannot prevent the passage of road vehicles or fails to alert the train driver to the hazard.  
The potential causes of this Hazardous Event can be grouped into three categories:  
1. Railway failure: A breakdown or malfunction in the rail-side safety systems allows the train to pass through an unprotected LC;
2. LC failure: A failure or malfunction of the roadside LC protection systems permits vehicles to cross the LC as a train approaches;
3. Hazardous vehicle behavior: This includes cases where the road vehicle improperly enters the track due to driver error or failure.  
The fault database analysis identified Root Events (REs) for each fault type. In the case of railway failure, the following REs were found:  
* Human error by the train driver (RE1);
* Failure of the train detection pedal (RE2);
* Logic and control system failure at the LC (RE3). LC failure can occur due to the following:
* Barrier malfunction (RE5);
* Acoustic signal failure (RE6);
* Warning light failure (RE7);
* Vandalism (RE4). Lastly, road vehicle driver errors can be linked to the following:
* Vehicle breakdown (RE8);
* Driver rushing or distraction (RE9).  
The structure of the fault tree illustrating these relationships is shown in Figure 4.  
The probability that each of the REs occurs at the train passage at the generic LC (i.e., at the single activation of the LC) has been calculated using fault data available through Equation (1).  
\[p=\frac{N_{ev}\cdot n_{TTR}}{n_{LC}\cdot n_{t,\text{year}}} \tag{1}\]  
where \(N_{ev}\) is number of events occurred; \(n_{days}\) is number of days to repair; \(n_{LC}\) is number of LCs compatible with the fault; and \(n_{t,\text{year}}\) is number of trains/year for the LC.  
Figure 3: Number of LC faults (N) per year and mean time to repair (MTTR) per part of the system.  
The fault tree has been adapted for each class of LC, assuming a failure rate of 100%, where LC does not have a specific safety barrier (e.g., no barriers or no warning lights and acoustic signal).  
Where data were not available, the following methodologies were used:  
* Human error probability assessment methodologies, like HEART methodology [42];
* Statistical analyses and expert judgments.
## 5 Key 6G Technologies
### Improved Wireless Interface
#### 5.2.9 Holographic Radio for Intelligent EM Space in 6G  
Holographic radio, employing holographic interference of electromagnetic waves, dynamically reconstructs EM space with precise real-time control. This innovative spatial multiplexing technique, using a spatially continuous microwave aperture, meets the demands for ultra-high spectral efficiency (SE), traffic density, and capacity. Holographic MIMOrepresents the ultimate form of a multi-antenna system with a finite aperture [157; 168]. Contrary to viewing interference as a drawback, holographic radio leverages interference as a valuable resource, promising enhancements in energy efficiency (EE) [169]. Additionally, it can save overhead in channel state information (CSI) or channel estimations by obtaining RF spectral holograms of transmitting sources through holographic interference imaging.  
Holographic radio is poised to play a vital role in a number of applications, including high-precision location, wireless power supply, smart manufacturing, and vast IoT device data transfer. Overcoming the technical challenge of realizing a continuous aperture antenna array is crucial for holographic radio. There are two main methods for achieving fast and efficient wireless communication. The first is through the use of re-configurable holographic surfaces (RHSs) [170; 171], which involve densely packing sub-wavelength unit cells. The second approach involves employing tightly coupled arrays of broadband active antennas [157] that are facilitated by high-power uni-traveling-carrier (UTC) photodetector-coupled antenna arrays. Both of these methods are designed to ensure low-power and low-cost consumption while achieving high performance [169; 172].  
Although there have been some advancements in the field of holographic radio communication, it still faces some challenges. One of the main issues is the lack of a strong theoretical foundation for this technology. Additionally, there is a need for dependable channel models that can be used in practice. Another challenge is processing the huge volumes of data produced by holographic radio systems with high reliability and low latency. All of these challenges must be overcome in order to fully realize the potential of holographic radio communication.
## 3 Methodology
### Threat Model: Addressing Security Attacks on ECUs  
CAVs extensively use a wide range of wireless and physical communication channels and multiple sensors. These communication channels are vulnerable to various security attacks [19; 28; 29]. ECUs establish connections with various sensors and actuators, communicate with other ECUs, and engage with communication interfaces, enabling them to acquire and interpret data, make informed decisions, and manage the vehicle's systems effectively. The attack surface of CAVs refers to the collection of entry points, vulnerabilities, pathways, and methods that an intruder could exploit to launch a cyberattack on ECUs. These entry points can be classified into three main types (shown in Figure 1): physical access attacks, sensing layer attacks, and wireless communication attacks. Below are descriptions of the attack surfaces associated with these categories that could be used to infiltrate ECUs and carry out malicious actions.
## 3 Methodology
### Modified Delphi Method  
[PERSON] and [PERSON] [46] proposed the Modified Delphi Method (MDM), which was selected for this study. It supplemented the open-ended questionnaire test with extensive relevant literature and in-depth interviews with subject matter experts. It developed a structured questionnaire to replace the first Delphi method survey. In this study, we utilized an MDM questionnaire with three rounds. The initial phase included in-depth interviews and a literature review to develop a structured questionnaire [47]. The relevance of each determinant was then evaluated by experts (with 5 denoting the most significant and 1 denoting the least significant). After collecting the completed questionnaires and integrating and analyzing each determinant, a revised questionnaire was developed for the next round. In the next round, the mean, standard deviation, and interquartile range were utilized as assessment criteria to validate the consistency of the experts' opinions. Based on the determinants' means, the significance of the determinants was evaluated [48]. The mean represented each determinant's relevance. A mean of 3.5 suggested that the Delphi experts believed the determinants are significant. When the standard deviation was more than 1, it suggested a significant degree of numerical discretization and dispersion across expert opinions.
# Biocompatibility of Membranes Based on a Mixture of Chitosan and _Lythri herba_ Aqueous Extract
## 3. Results
### Membrane Evaluation
#### 3.2.3 FT-IR Spectroscopy Analysis of CS-Ly-Based Membranes  
FT-IR analysis was carried out to determine the main functional groups of chitosan (CS) and of the _Lythri herba_ lyophilized aqueous extract (Ly), as well as the interaction between certain groups of these two components of the CS-Ly mixed membranes.  
FT-IR transmittance spectra were recorded and analyzed for the membranes obtained from mixing the solution of CS in diluted acetic acid solution (1%) with solutions of aqueous extract of _Lythri herba_, so that, in the end, the analyzed samples had the following final composition: CS 1% with 0.5 g/L, 1 g/L and 2 g/L _Lythri herba_, respectively (Figure 4). As a reference, a simple CS membrane in 1% acetic acid was chosen. Samples from all membranes were cut to small sizes and placed in the appropriate crystal holder of a Perkin-Elmer Spectrum BX spectrophotometer.  
As shown in Figure 4, the CS-Ly membranes showed absorption bands common to those of the simple CS membrane at wavenumbers 3736 cm\({}^{-1}\), 2918 cm\({}^{-1}\), 2849 cm\({}^{-1}\) and 2358 cm\({}^{-1}\). Based on the literature data, the results can be interpreted as follows: the common transmittance band of all four samples at 3736 cm\({}^{-1}\) can be attributed to the O-H stretching vibrations of the -CH\({}_{2}\)-OH group or the glycosidic ring involved in intramolecular hydrogen bonds [63] that overlap with the N-H stretching vibrations of the primary amines in the samples subjected to infrared (IR) analysis. The corresponding common peaks at 2918 cm\({}^{-1}\) and 2849 cm\({}^{-1}\) are characteristic of the C-H vibrations of the  
Figure 3: Topography of membrane surfaces evaluated in white light or epifluorescence—CS1 membranes (**a**,**e**), CS 1–Ly 0.5 (**b**,**f**), CS 1–Ly 1 (**c**,**g**), CS 1–Ly 2 (**d**,**h**), \(\times 200\) (**a–d**) and \(\times 400\) (**e–h**) magnification.  
methine groups in the pyranose nuclei of CS, CS-Ly membranes and polyholozides from the lyophilized extract. The common peak recorded at 1650 cm\({}^{-1}\) is attributed to the \(\
u_{\text{(C=O)}}\) stretching vibrations of the C=O from the NH-CO-CH\({}_{3}\) group (amide I band) of CS and its mixtures [64], and the one at 1398 cm\({}^{-1}\) corresponds to the C-N (amide III) stretching vibration. The C\({}^{3}\)-OH and C\({}^{6}\)-OH groups present in the CS structure were characterized by the peaks recorded at 1044 cm\({}^{-1}\) and 900 cm\({}^{-1}\)[65], but after the formation of the membrane by mixing with lyophilized extract, these peaks were not found in the spectra of CS-Ly membranes (Figure 4). Additionally, the spectra of CS-Ly membranes exhibited two peaks of low intensity at 1536 cm\({}^{-1}\) and 1618 cm\({}^{-1}\), which can be attributed to aromatic rings. These peaks are suggestive of the presence of polyphenic acids, phenolic acids or tannins, which are specific to the chemical composition of the lyophilized aqueous extract (Ly).
# Ionospheric Narrowband and Wideband HF Soundings for Communications Purposes: A Review
## 3 State of the Art of Sky Wave Sounding
### Antarctica Project  
The continent and the seas around the Antarctica are a natural laboratory of great interest for the scientific community. Several sensors are deployed to perform experiments for biology, geology and physics purposes with the aim to maintain an historic series or to carry out experiments that cannot be reproduced anywhere else on the Earth. The information obtained from these remote sensors should collected manually by the research community or be transmitted through satellite when the radio link is available. La Salle ([[http://www.salleurl.edu/en/research](http://www.salleurl.edu/en/research)]([http://www.salleurl.edu/en/research](http://www.salleurl.edu/en/research))), together with Observatori de l'Ebre (OE) ([[http://obsebre.es/en/research](http://obsebre.es/en/research)]([http://obsebre.es/en/research](http://obsebre.es/en/research))), both part of the Universitat Ramon Llull (URL) ([[http://www.url.edu/en/research-and-innovation](http://www.url.edu/en/research-and-innovation)]([http://www.url.edu/en/research-and-innovation](http://www.url.edu/en/research-and-innovation))), have been partners of a research project on the Antarctica for remote sensing and sky wave digital communication modem design for more than ten years [57].
# Numerical Analysis of the Bottom Thickness of Closed Rectangular Tanks Used as Pontoons
## 4 Discussion  
This paper presents calculation results for closed monolithic rectangular tanks performed in one stage and analyses the impact of bottom plate thickness on the distribution and values of deflections and bending moments in the considered system. No relevant results have been found in the literature for this type of structure.  
Since there are still problems related to the analysis, design and execution of concrete floating structures, the matter is considered to be challenging [35]. Most of the available and constructed reinforced concrete floats consist of a box and a covering plate. However, this approach is uncertain, since each contact can be a potential spot through which water gets inside [36]. The closed rectangular tank analysed in the paper is an effective solution that eliminates the possibility of water getting inside the structure [7; 34]. Tight filling of the box with polystyrene means water that could possibly get inside has no place to accumulate.  
By taking into account in static calculation the interaction of the tank structures with Styrofoam filling treated as an elastic foundation, all points of the structure see the reduction in the values of bending moments, sometimes even by approximately 30-40%. Including the Poisson's ratio \(\
u\
eq 0\) in calculations results in obtaining, for the central parts of plates (beyond the edges of the tank), the values of bending moments higher than calculated for \(\
u=0\). Including the Poisson's ratio in static calculation in closed monolithic tanks does not affect the values of bending moments occurring on the edges. Parameters such as \(\
u\) and \(K\) do not affect the calculation related to the so-called freeboard [33].  
Pontoons are structures exposed to numerous actions that are often difficult to define. That is why the tests that are carried out on life-size structures and in the form of case studies [7; 34; 37] are even more valuable. Publications [7; 34] include calculations of a unique reinforced concrete closed rectangular tank, which was made in the form of a life-size model and subjected to testing. The tank has walls of a constant thickness and a diaphragm in the middle of its length. Therefore, scientific considerations based on the finite difference method are subject to model verification. Figure 10 shows a prototype closed rectangular tank in the construction phase and during launching.  
For undeveloped floodplains, amphibious construction is an alternative to traditional construction [38; 39]. Reinforced concrete pontoons as supports for structures can be successfully used. Their significant weight has a positive effect on stability and buoyancy calculations.
# Pipelined Stochastic Gradient Descent with Taylor Expansion
## 3 Proposed Methods
### Computation and Communication Complexities  
In this section, we analyze and compare the computation complexity and communication complexity of SSGD, ASGD, and TaylorPipe [17]. Let \(H\) denote the number of neurons in a layer, which is assumed to be the same for all layers in a fully connected DNN model.  
\(L\) represents the number of layers in the model, \(M\) indicates the number of instances in a mini-batch, and \(T\) is the number of mini-batches in the training data. The computation complexity of the vanilla SGD for one epoch is \(\mathcal{O}\big{(}H^{2}LMT\big{)}\).  
When \(N\) computing nodes are used in parallel, the computation complexity for SSGD and ASGD on each computing node is \(\mathcal{O}\big{(}H^{2}LMT/N\big{)}\) since each computing node processes \(T/N\) mini-batches. In ASGD, as the parameter server updates the master model after each mini-batch, it requires \(\mathcal{O}\big{(}H^{2}LT\big{)}\) operations. On the other hand, it requires \(\mathcal{O}\big{(}H^{2}LT\big{/}\kappa\big{)}\) operations for the master model update in SSGD, as the parameter server updates the master model after every \(\kappa\) mini-batches. In TaylorPipe, each computing node processes all \(T\) mini-batches, but only for \(L/N\) layers, so the computation complexity becomes \(\mathcal{O}\big{(}H^{2}LMT/N\big{)}\), which is the same as the cases of SSGD and ASGD. However, TaylorPipe does not require additional model synchronization because each computing node updates the master model directly.  
The model synchronization in ASGD and SSGD requires the communication between the parameter server and all \(N\) computing nodes. Therefore, the communication complexity of ASGD is \(\mathcal{O}\big{(}H^{2}LT\big{)}\), while that of SSGD is \(\mathcal{O}\big{(}H^{2}LT\big{/}\kappa\big{)}\). On the other hand, since the master model and local models reside in the same computing nodes, no communication is required for the model synchronization in TaylorPipe. However, the results of the forward and backward passes are transmitted to the adjacent computing nodes in parallel, which results in the communication complexity of \(\mathcal{O}(HMT)\).  
The computation and communication complexities of SSGD, ASGD, and TaylorPipe are summarized in Table 1. Though the computation complexities in a computing node for all three methods are the same, TaylorPipe has the advantage in communication, since \(HM\) is usually much smaller than \(H^{2}L/\kappa\) in a large-scale DNN training.
# NMR-MPar: A Fault-Tolerance Approach for Multi-Core and Many-Core Processors
## 6 Materials and Methods
### Fault-Injection Details  
The fault-injection technique proposed in this approach to emulate SEU is an SWIFI technique. As was previously stated, the approach validated in our previous works concerning fault-injection on multi-core processors [7; 37; 38; 39] is based on Code Emulated Upset (CEU) principles [47], which reproduce, without intrusion, the effects of SEUs. This is achieved by the assertion of asynchronous interrupt signals. The execution of the interrupt handler produces the error in a randomly-chosen target. The CEU approach uses an external device to produce an interruption that emulates a bit-flip in a targeted memory cell. In the case of multi-/many-core processors, it is possible to benefit from the multiplicity of cores by using one of them as a fault-injector while the others run the chosen application. More details about the implementation of the fault-injector tool can be found in our work [48].  
In order to produce the fault-injection by interrupting the targeted core, the portal NoC communication primitive is used. Thus, the configuration of one portal per cluster (portal_fi) is needed for fault-injection purposes. The RM0 of IO Cluster 0 is in charge of configuring the master part of each portal. Note that, although the device is divided into two independent global parts, the communication between clusters is always possible so that IO Cluster 0 could communicate with the 16 CCs. The portal is used to interrupt the CC that contains the selected PE core to perform the fault-injection.  
To emulate a bit-flip in the selected register, the fault injector must interrupt the selected core. To achieve this goal, at the random instant within the nominal duration of the application, the fault-injector writes the fault-injection variables, random PE, random address and random bit in the portal_fi of the CC that contains the selected core. This causes an interruption of the RM, which immediately assigns the execution of an interruption handler to any one of the PEs. The assigned PE reads the information in the portal_fi, which contains the selected core, register and bit to modify. If it is the targeted core, it changes the bit in the selected register. Otherwise, it sends an inter-processor interrupt to the corresponding PE, which performs the bit-flip emulation.  
During fault-injection campaigns, only the emulation of one SEU per execution was considered to be injected in the targeted register belonging to one of the PE cores used by the application. In order to avoid the propagation of errors to the next execution, the HOST resets the platform and reloads the code to the MPPA processor after each run. Hence, the random variables required by the fault-injector are provided by the HOST.
# Monitoring of [PERSON]'s Disease Based on Wireless Sensing Technology
## 3 Principle of Wireless Sensing Technology
### Csi  
In order to eliminate the adverse effect of a multipath effect on wireless signal transmission, the MSP described in this paper uses orthogonal frequency division multiplexing (OFDM) modulation technology to decompose the data stream to be transmitted into several independent sub-data streams, that is, multiple subcarriers, and then transmits them in parallel, which can effectively eliminate the inter-symbol interference caused by the multipath effect in high-speed data stream transmission. At the same time, OFDM modulation technology can also greatly improve the data transmission efficiency. Because there are multiple subcarriers, each subcarrier channel is independently available, which also increases the amount of data to extract more information [20].  
Figure 1: Indoor propagation model of wireless signal.  
Multiple input multiple output (MIMO) is supported by OFDM modulation technology [21]. The channel model of the MIMO system in the frequency domain can be expressed as  
\[Y=\mathbf{H}X+N \tag{3}\]  
where \(Y\) represents the receiving signal, \(X\) represents the transmitting signal, \(N\) represents the environmental noise, and \(\mathbf{H}\) represents the state matrix of the wireless channel, and its dimensions are \(N_{T}\times N_{R}\times N_{C}\). \(N_{T},N_{R},\text{ and }N_{C}\), respectively, represent the number of transmitting antennas, receiving antennas, and subcarriers.  
CSI is essentially a representation of the frequency response of each subcarrier channel. For each independent subcarrier channel, its frequency response can be expressed as  
\[H_{k}(f_{k})=\|H_{k}(f_{k})\|e^{\text{i}arg(H_{k}(f_{k}))}\ (1\leq k\leq N_{C}) \tag{4}\]  
where \(f_{k}\) represents the center frequency of the Kth subcarrier, \(\|H_{k}(f_{k})\|\) represents the CSI amplitude information of the Kth subcarrier, and \(arg(H_{k}(f_{k}))\) represents the CSI phase information of the Kth subcarrier.  
After continuous data collection over a period of time, CSI data can be obtained through the channel estimation formula [22].  
\[\hat{H}\approx\frac{Y}{X} \tag{5}\]