esa-sceva/satcom-chunk-collection huggingface dataset:
# Comparison of ANN and ANFIS Models for AF Diagnosis Using RR Irregularities
## 2 Materials and Methods
### Study Population and ECG Measurements  
The ECG recordings of 120 samples from 60 patients used in this research included 40 NSR, 40 PAF, and 40 AF cases. All recordings were made by cardiologists in comparable conditions with patients maintained at rest and in a comfortable position. Signal recordings were acquired at a sampling rate of 1000 Hz with 12-bit resolution using lead II for a 2.5-min duration [24]. [PERSON] et al. (2022) showed the list of HRV parameters from the ECG signals of existing research works, which exhibited that the total of all signal times (number of subjects \(\times\) recording duration) was between 50 min and 240 h [25]. Each sample in this research contained approximately 150 segments. In order to ensure the sufficiency of the datasets, the data augmentation technique was employed and new data sets from existing data were generated. Each group of data was combined and randomly segmented into 2.5-min intervals. So, in this research, a total of 240 samples, or 36,000 segments, were used. The total of all signal times was 600 min.  
This study was approved by the Human Ethics Committee, Faculty of Medicine, Thammasat University (EC no. MTU-EC-IM-2-230/63) on 27 October 2020. The patients were individually matched concerning age (NSR: 33.85 \(\pm\) 20.66, PAF: 68.43 \(\pm\) 11.47, AF: 69.20 \(\pm\) 9.47), gender: female (NSR: 25%, PAF: 58%, AF: 55%), congestive heart failure (NSR: 0%, PAF: 5%, AF: 10%), hypertension (NSR: 15%, PAF: 63%, AF: 65%), diabetes mellitus (NSR: 0%, PAF: 20%, AF: 25%), and vascular diseases (NSR: 0%, PAF: 5%, AF: 10%).
### Objective and Approach  
Therefore, in this study, rather than simply investigating the degree of expectations and purchase intentions, the aim was to examine a method to investigate the anticipated UX that users gain from packaging designs in an exploratory and qualitative manner. As a method for investigating the content of anticipated UX in an exploratory manner, we adopted the evaluation grid method, which is an interview and analysis technique that can clarify the evaluation structure that people have for the evaluation target and examine the structure of the design elements of the package and the appeal and sense of expectation that can be gained from them. To examine the applicability of the evaluation grid method for the anticipated UX analysis, we used boxed flour confections and sunscreen as examples. We selected the confections as products with strong hedonic attributes and the sunscreen as products with strong practical attributes.  
The evaluation grid method was originally proposed in the fields of architecture and environmental psychophysiology as a method that could be used to evaluate spaces and environments, based on the Repertory Grid Method [27] in the field of clinical psychology, which was proposed by [PERSON] [28]. This method aims to extract the parts related to evaluating spaces and products from the diverse cognitive structures unique to each individual, based on the Personal Construct Theory. This method is also used to understand user needs in product development and marketing. For example, [PERSON] et al. [29] used the evaluation grid method to analyze the UX of mobile apps. Therefore, we used the evaluation grid method to analyze the anticipated UX obtained from the package, as we thought it would be easy to understand the subjective experiences of various users. In addition, the evaluation grid method allows us to grasp the hierarchical structure of users' evaluations of the target theme, so we can understand the causal relationships between the higher- and lower-level concepts that make up the anticipated UX. In other words, by focusing on these relationships, we can speculate on the relationship between what kind of package elements will lead to what kind of experience. This would be useful for creating package design concepts.  
This research suggests using the evaluation grid method to examine the anticipated UX that can be obtained from a package. As we have seen, it will contribute to the construction of a new method for considering package design guidelines from the perspective of the anticipated UX, which has not been considered much until now.
# A Cognitive Anycast Routing Method for Delay-Tolerant Networks
## 3 Anycast Routing
### CSG Routing Method
#### 3.1.2 Cognitive Network Controller  
The CNC [18] defines an SNN architecture of \(2(K-1)\) neurons, where \(K\) is the number of outbound link decisions (also known as actions) that are available for the bundle. Each action is represented by one excitatory neuron: \(N_{1},\ldots,N_{K}\) connected as a mesh with synapses \(w_{N_{i},N_{j}}\) in both directions for any two neurons \(i,j=1,\ldots K\), \(i\
eq j\). The goal of the other neurons is to provide membrane potential regulation as the excitatory signals of the core neurons can lead to potential saturation. This is achieved by making the neurons \(M_{1},\ldots,M_{K-2}\) inhibitory with directed synapses toward the core neurons: \(w_{M_{i},N_{j}}\), \(i=1,\ldots,K-2\), \(j=1,\ldots,K\).  
To make a routing decision, the SNN is started by applying identical external stimulus \(I_{ref}\) to all neurons. The SNN activity is then observed to determine the time of emission of the neurons' second spike. The first spike is used for bootstrapping the SNN as that spike carries the effect of the current synaptic connection values to the post-synapse neurons. Once the neuron that emits the earliest second spike is detected, the routing decision is given by the link being represented by that neuron, i.e., the CNC decides to use the link \(a=i^{*}\), provided that \(N_{i^{*}}=\operatorname*{argmin}_{N_{i}}\ t^{(2)}(N_{i})\quad;i=1,\ldots,n\), where \(t^{(f)}(x)\) is the firing time of the \(f\)-th spike of neuron \(x\). If multiple neurons are detected to emit their second spike at the same time, the link decision is carried out randomly among those options. Furthermore, to prevent local minima, the routing decisions are modulated by a random walk with a (small) probability of \(P_{w}\).
# Artificial Intelligence Applications for MEMS-Based Sensors and Manufacturing Process Optimization
## 4 Artificial Intelligence Application in MEMS System: Current Trends
### AI Application in MEMS-Based Sensors
[72] developed an automated defect recognition system based on the Faster R-CNN Inception V2 COCO model by using a plenoptic image of the wafers for surface defect detection. The proposed method can be used for early fault detection at wafer and component levels of MEMS, reducing the design time significantly. Thus far, all the discussed papers are primarily related to industrial, automotive, or consumer-related use cases, which show promising results for AI applications in MEMS-based sensor applications. AI application for MEMS (BioMEMS) in healthcare is another potentially colossal market [73]. Examples of general applications of MEMS in healthcare can be in a pedometer, hearing aid, body gateway, lab on a chip, blood pressure, etc. [74]. [PERSON] et al. [75], and [PERSON] et al. [76] have discussed AI applications to diagnose several diseases using MEMS sensor-based smart diagnostic devices using Mechanobiology, which uses biosensors. MEMS are used here for finding external stimuli using force spectroscopy. NN can detect environmental factors, such as viruses or bacteria, along with the traditional method. To summarize, in most applications, different RNN and CNN models performed better than the classical statistical models.
# Ensemble Radar-Based Rainfall Forecasts for Urban Hydrological Applications
## 3 Results
### Sewer Flow Simulations  
The hydrodynamic model was verified using radar rainfall and the additional rain gauge data within the urban area as input. Figure 9 presents the results comparing the measured flow with flow simulated using radar data and Figure 10 shows the results comparing measured flows and flows simulated using gauge data. The simulation using gauge data presents a slightly better result than using radar data. The results show that the hydrodynamic model simulated the flows accurately in many cases. To exclude dry periods, the RMSE was only calculated for measured flows over the threshold of 0.1 m\({}^{3}\)/s. The RMSE for the radar flow simulations is 0.0956 m\({}^{3}\)/s and for the gauge flow simulation is 0.0838 m\({}^{3}\)/s using a time period from 15 April 2008 to 31 December 2008.  
Figure 8: Area beneath ROC curves for all the events using radar ensembles and STEPS ensembles and thresholds 0.1 mm/h (**a**), 1 mm/h (**b**) and 3 mm/h (**c**).  
Figure 10: Measured flows (Q\({}_{\rm m}\)) and gauge simulated flows (Q\({}_{\rm G}\)) from 1 July 2008 until 30 September 2008.  
Figure 9: Measured flows (Q\({}_{\rm m}\)) and radar simulated flows (Q\({}_{\rm R}\)) from 1 July 2008 until 30 September 2008.
## 5 Discussion
### Sediment Export Estimation  
According to the results of sediment export estimation, it was found that the primary influence of rainfall erosivity and LULC types in the RUSLE model affect sediment export under three different scenarios. The rainfall erosivity can explain the linear relationship with the sediment export from about 27% in Scenario III (Economic crop zonation) to 96% in Scenario II (Maximization of ecosystem service values). These findings are consistent with the previous studies [56; 57; 58; 59; 60].  
The contribution of the predicted LULC under three scenarios on sediment export between 2020 and 2029 indicated that miscellaneous land causes the highest average sediment export. Meanwhile, forest land generates the lowest average sediment export. This finding was consistent with the previous study of [PERSON] et al. [14]. They found that miscellaneous land (bare land and abandoned mine) created the highest average sediment export, with a value of 659.72 tons/km\({}^{2}\). At the same time, evergreen forest generated the lowest average sediment export, with a value of 0.01 tons/km\({}^{2}\), in the Klong U-Tapao watershed, Songkhla Province, Thailand. Likewise, [PERSON] et al. [74] found that the highest sediment export per unit of area was observed from miscellaneous land (bare land), while the highest contribution of the total sediment that reached the surrounding water bodies was from cultivated land (40.7%). Similarly, [PERSON] et al. [75] found that decreases in miscellaneous land (bare land) significantly reduced sediment export in the Qiantang River Basin, China. In contrast, increases in agricultural land, such as cropland and garden plots, increased sediment export in the studied watershed.
## 3 Absorption Characteristics
### Polarization Independence and Oblique Incident Angle Stability  
Its polarization insensitivity was evaluated to confirm the suggested MMA's absorbance efficiency. Figure 10a,b demonstrate the absorbance properties of various incident angles (\(\phi\)) for TM and TE modes. In the TE mode, the \(z\)-axis determines the propagation direction of the wave, and its location along the \(z\)-axis defines the magnetic field vector (Hz). The \(x\) and \(y\)-axes represent the electric (E\({}_{x}\)) and magnetic field vectors (H\({}_{y}\)). Moreover, the TM mode's electric field vector (E\({}_{z}\)) is long in the direction of wave propagation. The electric (E\({}_{y}\)) field vector and the magnetic (H\({}_{x}\)) field vector corresponding along the x and y axes. The proposed MMA obtained an exceptional absorbance characteristic for polarization incidence angles (\(\phi\)) up to 90\({}^{\circ}\) due to its axial and rotational symmetry. The EM wave hits the MMA at an oblique angle, while all previous results were at a standard angle (\(\theta=0^{\circ}\)). As a result, the explanation of oblique incidents absorbance behavior is also essential. The MMA structure is designed to have an oblique incidence angle (\(\theta\)) between the z-axis and the direction of wave propagation. Figure 11a,b illustrate the absorbance  
Figure 9: (a) Co-polar and Cross-polar component (b) The PCR value of x-polar and y-polar of the incident wave.  
curves of both modes of TE and TM for theta (\(\theta\)) up to 70\({}^{\circ}\), where above 70% absorbance is achieved.
# A Compact Wearable Textile Antenna for NB-IoT and ISM Band Patient Tracking Applications
## 2 Antenna Design Methodology
### Bending Analysis of Proposed Antenna  
The constraint for wearable antennas is physical conformability, which proves their capability to tolerate an evident bending and a convenient integration of antenna on the clothes of the human body [34]. The proposed antenna is designed to integrate into the wearable clothes of patients and can be placed on the human body's chest, arm, or wrist. The average diameter of the arm for newborn babies, kids, and adults is 93 mm, 140 mm, and 350 mm, respectively [34]. Figures 6 and 7 show different bending radii of the cuboid phantom body and corresponding results, respectively. Here, the thickness of the skin, fat, muscle, and cotton fabric is 2 mm, 5 mm, 13 mm, and 1 mm, respectively [31]. The results clearly show that due to the wideband nature of the designed antenna, it can easily handle a minimum bending of 25 mm, while the wrist of a newborn is not more than 35 mm.  
Consequently, reflection coefficients at different curvature radii (25 mm, 35 mm, and 45 mm) of the antenna are shown in Figure 7. It can be noticed that the antenna experiences detuning when placed at the cylindrical multi-layer phantom. When the antenna was placed at a 25 mm radius phantom, it experienced maximum bending, and all the reported resonances shifted to the lower side.  
At 35 mm and 45 mm radii, the antenna experiences less detuning. Since the designed antenna is wideband, it covers all the frequency bands (1.8 GHz, 2.45 GHz, and 5.8 GHz). Even after a little detuning due to the bending, this antenna is a suitable candidate for wearable applications due to its endurance to the bending at different radii.  
Figure 6: Analysis of bending states (at different radii) of the proposed antenna on cuboid phantom at (**a**) \(R_{1}\) = 25 mm, (**b**) \(R_{2}\) = 35 mm, (**c**) \(R_{3}\) = 45 mm.
## 4 Analysis of the Vibration Suppression Mechanism of the Deflector Plate
### Validity Verification of Numerical Simulation  
In order to verify the validity of the numerical simulation, we compared the numerical simulation calculation results with the wind tunnel test results. The verification result is shown in Figure 23.  
It can be seen from Figure 23 that the locking range of VIV wind speed obtained by the wind tunnel test at a +3\({}^{\circ}\) wind attack angle was 5.24 m/s\(\sim\)6.72 m/s, which was consistent with the simulation results. Regarding the amplitude of the vertical VIV, the change law of the vertical amplitude with the wind speed obtained from the wind tunnel test is consistent with the numerical simulation results. The wind tunnel test obtained a maximum vertical amplitude of 75.54 mm and an average vertical bending amplitude of 37.44 mm. The numerical analysis obtained a maximum vertical amplitude of 85.36 mm and an average vertical amplitude of 40.17 mm. The maximum VIV amplitude difference between the test and the numerical simulation was 11.0%, and the average VIV amplitude difference was 6.7%. At a +5\({}^{\circ}\) wind attack angle, the VIV wind speed locking range obtained by the wind tunnel test was 5.01 m/s\(\sim\)6.69 m/s, consistent with the simulation results. Regarding the amplitude of the vertical VIV, the change law of the vertical amplitude with the wind speed  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Condition**} & \multirow{2}{*}{\(\triangle\)**t (s)**} & \multicolumn{3}{c}{**Calculation Results**} \\  & & \(\mathbf{C_{H}}\) & \(\mathbf{C_{V}}\) & \(\mathbf{C_{M}}\) \\ \hline \multirow{3}{*}{Original section} & 0.001 & 0.6204 & 0.2658 & \(-\)0.0102 \\  & 0.0005 & 0.6317 & 0.2739 & \(-\)0.0136 \\  & 0.0001 & 0.6453 & 0.2872 & \(-\)0.0140 \\  & 0.00005 & 0.6457 & 0.2879 & \(-\)0.0146 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Results of the irrelevance verification of the time step.  
Figure 23: Comparisons between test value and calculated value.  
obtained from the wind tunnel test is consistent with the numerical simulation results. The wind tunnel test obtained a maximum vertical amplitude of 98.23 mm and an average vertical amplitude of 55.70 mm. The numerical analysis obtained a maximum vertical amplitude of 107.14 mm and an average vertical amplitude of 58.85 mm. The maximum VIV amplitude difference between the test and the numerical simulation was 8.3%, and the average VIV amplitude difference was 5.4%. To sum up, the mesh and the numerical analysis algorithm adopted in this paper were accurate. They can realize the simulation of the VIV of the main girder section of double-deck truss girders.
# Global Power Dynamics in the Contemporary Space System
## 5 System Dynamics--Global Power Dynamics
### Expansion of the National Space Capabilities  
The initial observable tendency in contemporary global power dynamics concerning the space system is the increasing development of national space programs, as evidenced by the allocation of resources for space-related activities and the advancement of novel space capabilities. There is substantial evidence indicating the interest of states in outer space.  
In accordance with the Space Technology Ladder framework, which delineates the milestones achieved by nations in their pursuit of national space technology capability, the establishment of the inaugural national space agency constitutes the initial step [67]. From 2000 to 2020, 37 national space agencies were established, including those in Japan, Iran, Mexico, South Africa, and Portugal. A similar trend was observed in the subsequent years, with 16 space agencies being established between 2014 and 2019, including those in Australia, Egypt, Turkey, and Saudi Arabia [76]. In recent years, a growing number of countries have followed the same path, including Luxembourg (2019), Greece (2019), Uzbekistan (2019), Portugal (2019), Rwanda (2021), Costa Rica (2021), Spain (2023), and South Korea (2024).  
Another indicator is the development of national space policy, directives, and programs that provide guidance in the development of space activities. In the preceding decade, the majority of space powers, including the United States (US Space Priorities Framework (2021) and the Artemis Program (2019)), China (China's Space Program: A 2021 Perspective (2022)), European Union (EU Space Programme (2021-2027)), India, and Japan have updated their space policies and programs. Furthermore, a considerable number of emerging and smaller powers have formulated novel space policies over the past two decades.  
Government expenditure on space programs has increased significantly since the conclusion of the Cold War. From 1990 to 2016, spending rose from USD 32 billion to USD 62 billion, and reached a new historic high of USD 117 billion in 2023, representing a 15% increase from the previous year (2022). The United States Government allocated approximately USD 79.7 billion to its space programs in 2024, positioning it as the nation with the highest space expenditure globally [46]. China is the second-largest space program, with an estimated expenditure of USD 19.9 billion, exhibiting an 11% compound annual growth rate. Russia's investment in its space program stands at USD 3.9 billion. Additionally, seven other countries and the European Union collectively allocate more than USD 1 billion to their respective space programs, including Japan (USD 6.8 billion), France (USD 3.7 billion), Germany (USD 2.8 billion), Italy (USD 2.65 billion), India (USD 1.89 billion), the United Kingdom (USD 1.46 billion), and South Korea (USD 1.03 billion) [46].
# Channel Access in Wireless Smart Grid Networks Operating under ETSI Frame-Based Equipment Rules
## 3 Channel Access
### Frame-Based Equipment  
The FBE channel access rules are part of the LBT scheme defined in ETSI EN 301 893 [6]. In LBT, the nodes perform a clear channel assessment (CCA) immediately before each transmission. The CCA is performed during a single observation slot, which lasts at least 9 \(\upmu\)s. For FBE nodes, the start of a transmission signifies the beginning of the duty cycle, called a fixed frame period (FFP). FFP can last from 1 to 10 ms and a node can manipulate its duration, but changes cannot occur more often than once every 200 ms. Each channel access duration is limited by the channel occupancy time (COT), which in turn cannot exceed 95% of the FFP. During a single COT, a node can perform multiple transmissions without repeating the CCA only if the gap between consecutive transmissions is not greater than 16 \(\upmu\)s. Otherwise, an additional CCA is required to determine the status of the channel. A receiver can skip CCA and immediately respond with an acknowledgment after successful data reception, but only if the acknowledgment duration does not exceed the COT. The time between the end of the COT and the beginning of the next FFP is called the idle period and must be at least 5% of the COT, with a minimum of 100 \(\upmu\)s. If a CCA operation is unsuccessful (i.e., indicative of a busy channel), an FBE node must refrain from transmission (referred to as muting) and perform a CCA before the next FFP. Figure 1 illustrates the operation of FBE and the various time periods. Henceforth, we refer to this mode of operation as standard FBE.  
Standard FBE and most variants described below follow a periodic FFP scheme, so the synchronization of node COTs impacts performance. The case in which all nodes start their FFPs simultaneously is referred to in the literature as the synchronous mode. The benefits of this approach are related to the synchronization of base stations in cellular systems [10]. However, in unlicensed bands, this can lead to collisions (Figure 2a). An alternative is the asynchronous mode, in which nodes start their FFPs independently, which we model by stating that each node is delayed by a shift. We also introduce the concept of perfect node coordination--the state in which the shift of nodes is optimally configured so that they can transmit in consecutive FFPs without collisions. An example of perfect node coordination is shown in Figure 2b.  
Figure 1: Example of standard FBE operation. A successful CCA precedes the first COT. The second CCA is unsuccessful, hence the node refrains from transmitting in the second FFP.