esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Proposed Bearing Fault Diagnosis Method using Acoustic Emission Signals  
In this section, a novel method for diagnosing bearing faults under variable rotational speeds using AE signals adopting Short-time Fourier Transform (STFT), CNN model, and SLS is presented. Figure 1 shows the overall process of the proposed method. The proposed method consists of three major stages. In the beginning, the acquired raw AE signals are split into 0.1 s fixed cycle signal segments. Then, STFT is applied to AE signal segments to create spectrogram images as the representation method in the time-frequency domain. After that, image normalization is applied to the created spectrogram images as a way of enhancing their representation ability. Besides, the spectrogram images are standardized to fit the CNN model. Secondly, the EfficientNet CNN model randomly initializes its parameters and is pre-trained by the spectrogram images. During the training process, the SLS optimizer is used to increase the probability of convergence and accuracy in fault classification. Then, the trained CNN model is used to classify bearing faults automatically in the final stage.
## 4 Discussion
On average, the calibration residuals of the two optical systems used in the proposed method (Smart-DX) and in clinical practice (OTS-CT) do not differ significantly in terms of accuracy (calibration residuals below 1 mm and \(1^{\circ}\)). Also, the two optical systems rely on two different types of tracking: OTS-CT detects markers in the blue range, while OTS detects reflective markers; the diameter of the two different markers was characterized using a Laser Tracker system (Leica AT960-MR, Hexagon) and we verified that there were no significant diameter differences (diameter median difference value (interquartile range) is 0.07 (0.11) mm). Nevertheless, the results of this study show that ETS alignment outside of the CT bulker is feasible with no or negligible difference with respect to the currently applied procedure, bringing along the indisputable advantage of limiting the occupancy time of the CT bulker.
# In-Plane Monolithic Integration of Scaled III-V Photonic Devices
## 2 Template-Assisted Selective Epitaxy  
A simplified schematic of TASE is shown exemplarily for a nanorod structure in Figure 2. The process is indeed not limited to this simple shape but has, amongst others, been applied to achieve micro-disks [31] or crossbar structures [28; 36]. The starting point of TASE is a Si structure patterned by standard Si processing techniques--i.e., in our case, e-beam lithography and HBr dry etching. Here, we use a standard SOI wafer, as it provides the ideal optical isolation of the photonic devices in the top layer from the Si substrate and allows for seamless integration with Si passive structures in the same layer. The etched Si structure is encapsulated in \(\sim\)200 nm SiO\({}_{2}\) by a combination of atomic layer deposition (ALD) and plasma-enhanced chemical vapor deposition (PECVD). Subsequently, a window is etched into this oxide layer at one or more locations of the patterned Si, whereby the Si is locally exposed again, as shown in Figure 2b. This allows us to partially remove the Si from one side with a well-controlled tetramethylammonium hydroxide (TMAH) wet etch. The resulting hollow oxide template with a remaining Si seed is depicted in Figure 2c. During the MOCVD growth step, the III-V material will nucleate on this Si seed and then continue to fill the SiO\({}_{2}\) template (d), adapting to its shape. By changing the precursor flow during growth or adding doping species, one may change the composition and/or the background doping either abruptly or gradually in situ during growth. This allows for the creation of in-plane heterojunctions or quantum wells orthogonal to the substrate orientation with a high-quality material interface, which is generally challenging in other techniques.  
In the following, two different devices will be used to illustrate the specific advantages of in-plane TASE growth for integrated photonics. Firstly, we will discuss its application to III-V/Si hybrid photonic crystal cavities, focusing on different device optimization steps;  
Figure 2: Schematic of TASE process flow. (**a**) Patterning of a SOI wafer by standard lithographic methods and Si patterning processes. (**b**) Deposition of an oxide layer (SiO\({}_{2}\)) which covers the Si structure. A window is etched into the SiO\({}_{2}\) layer to expose one end of the underlying Si. (**c**) The Si structure is partially etched back using TMAH, leaving a hollow template behind and exposing a small Si nucleation seed at one extremity. (**d**) MOCVD growth of the III-V material into this template, nucleating on the Si seed.  
secondly, we will illustrate the extension to electrically actuated devices with the example of an in-plane monolithic photodetector.
# Opportunistic Sensor Data Collection with Bluetooth Low Energy
## 5 Evaluation
### Sensor Node Lifetime  
Using the average current consumption results obtained in the previous section, it is possible to determine the theoretical lifetime of a battery-operated sensor node. Assuming a button cell battery of 230 mAh (such as the CR2032 model), and the same conditions assumed in the previous section, the sensor node lifetime is plotted in Figure 12, as a function of _advInterval_, and for different contact time values.  
As shown in Figure 17, with the advertising-based approach, it is possible to achieve a theoretical sensor node lifetime up to 5.33 and 3.02 years, for \(N=1\) and \(N=3\), respectively. Using the connection-based approach, and assuming error-free communication, the sensor node lifetime can be of up to 1.31 and 1.09 years, for \(N=1\) and \(N=3\), respectively, and for \(T_{contact}=45\) s.  
A theoretical value of \(T_{contact}=0\) s has also been evaluated for the connection-based approach, which provides an upper bound of the achievable sensor node lifetime in this approach. For this setting, the short size of the advertising packet used leads to a current consumption even lower than that of the advertisement-based approaches (which use a greater sized advertising packet) for the same value for \(N\). However, sensor node lifetime increases with BER in the connection-based approach, accordingly to the behavior assessed in the previous section. For high _connInterval_, high _advInterval_, and \(N=1\), sensor node lifetime increases by a factor greater than 3 for BER = \(10^{-4}\) compared with a BER = 0 scenario. However, sensor node lifetime increase with BER comes at the cost of lower amount of sensor data collected (see Section 5.3). Sensor node lifetime increases with _advInterval_. However, there exists a trade-off between sensor node lifetime and the amount of sensor data that can be collected during the contact time that depends on _advInterval_ (see Section 5.3). For BER = 0, the _connInterval_ parameter exhibits a negligible impact on both the average current consumption and the sensor node lifetime. In the presence of channel errors, _connInterval_ leads to significant performance difference only for high values for this parameter.  
Figure 17: Average sensor node lifetime, for the advertisement-based and connection-based approaches, as a function of _advInterval_, and for different \(N\), \(T_{contact}\) and BER values, and assuming a time between contacts of one day. For connection-based results, _connInterval_ = 4 s has been assumed.
# DDPG-Based UAV-RIS Framework for Optimizing Mobility in Future Wireless Communication Networks
## 2 System Model
\(\lambda\) and \(d\) denote the wavelength and antenna separation while \(F_{x}\) and \(F_{y}\) are the reflecting elements of RIS along the X-axis and Y-axis. We assumed LoS links from GBS to UAV-RIS and from UAV-RIS to GUs; \(g(t)\) in (10) is the cascaded channel gain of GBS-(UAV-RIS)-GU and is calculated as  
\[\parallel q_{\text{UR}}[N]-q_{F}\|^{2}\leq V^{2},q_{\text{UR}}[1]=q_{0}, \tag{1b}\]7  
where \(H\) is the UAV-RIS to GU channel gain and \(h_{1}\) is the GBS to UAV-RIS channel gain. Furthermore, \(v_{g}\) and \(v_{u}\) in (10), respectively, are the received array vector from GBS to the UAV-RIS and the transmit array vector from UAV-RIS to the \(k\)th GU at time \(t\), and can be formulated [35] as  
\[\parallel q_{\text{UR}}[N]-q_{F}\|^{2}\leq V^{2},q_{\text{UR}}[1]=q_{0}, \tag{1b}\]8 \[\parallel q_{\text{UR}}[N]-q_{F}\|^{2}\leq V^{2},q_{\text{UR}}[1]=q_{0}, \tag{1b}\]9  
Here, variable \(\theta\) denotes the relative phase difference between the received signal at the GBS and the first UAV-RIS element, while \(\beta\) represents the relative phase difference among the elements of the UAV-RIS reflected beams towards the GUs. For the sake of fairness, every user in the group is allocated the same bandwidth (B), and each UAV-RIS in the network utilizes the same frequency band simultaneously. By combining (4), (9), and (10), the signal-to-interference plus noise ratio (SINR) from each UAV-RIS to GUs in the HetNet during time instant \(t\) can be expressed as follows:  
\[\parallel\text{q}_{\text{UR}}[n+1]-q_{\text{UR}}[n]\|^{2}\leq V^{2},n=1,\dots, N-1, \tag{2}\]0where \(P_{\text{UR}}\) is the transmit power of UAV-RIS to their GUs and \(B\) is the system bandwidth in the mmWave range. \(\psi\) and \(\sigma\) represent the network experiences interference and additive white Gaussian noise (AWGN), respectively. Based on Equation (14), the sum rate of GUs could be obtained as  
\[\parallel\text{q}_{\text{UR}}[n+1]-q_{\text{UR}}[n]\|^{2}\leq V^{2},n=1,\dots, N-1, \tag{2}\]1  
Here, \(\varpi\) represents the instantaneous SINR for each ground user, and the sum rate expression follows the Shannon capacity formula.
## 3 Results
### The Viability of Acidogenic Bacteria  
The most important qualitative parameter in yogurt is the viability of acidogenic bacteria [23]. The number of fermentative bacteria, including _Lactobacillus bulgaricus_ and _Streptococcus thermophilus_, which are known for fermenting sugar in milk into lactic and other organic acids, was measured in this assay. As shown in Figure 1D, the addition of TB contributed to improving the total viability of _Lactobacillus bulgaricus_ and _Streptococcus thermophilus_ in yogurt when compared to the control. The results showed that TB supplementation had an evident boosting impact on _Lactobacillus bulgaricus_ colony counts, with the highest _Lactobacillus bulgaricus_ count (18 \(\times\) 10\({}^{5}\) CFU/g) obtained after 5 h of fermentation in the sample containing 10 g of TB. Moreover, there was a dramatic reduction in the viable counts of _Lactobacillus bulgaricus_ in yogurt with 12 g of TB addition compared with yogurt with 10 g of TB addition, which was likely to be due to an increase in the production of metabolites as a result of increased metabolic activity. The accumulation of metabolites has a specific inhibitory effect on cell growth, which can lead to a reduction in bacterial viability [24]. Simultaneously, the quantity of _Streptococcus thermophilus_ declined gradually with the increase of TB addition, and yogurt with 4 g of TB addition (9 \(\times\) 10\({}^{5}\) CFU/g) had more than fourfold greater than plain yogurt (2 \(\times\) 10\({}^{5}\) CFU/g) and had the maximum amount of _Streptococcus thermophilus_ among all samples.  
In numerous circumstances, the health benefits of yogurt can be ascribed to the starter cultures (_Lactobacillus bulgaricus_ and _Streptococcus thermophilus_) [25]. Previous work demonstrated that a number of factors influence the survival of fermentative bacteria in yogurt, including formulation factors (pH and total titratable acidity, hydrogen peroxide, molecular oxygen, strains of probiotic bacteria and microbial interactions, ripening factors, salt, growth promoters, and food additives), process factors (types of inoculation, heat treatment, incubation temperature, and storage temperature), and packaging [26]. TB is a nutrient-dense food that is abundant in flavonoids, dietary fibers, proteins, vitamins, and minerals. This indicates that TB could be used as a rich growth medium for yogurt bacteria to promote its growth and metabolic processes. This is a significant finding because increasing the amount of viable bacteria in yogurt can improve the rate of protein digestion and nutritional value [27].
# DEM Analysis of Track Ballast for Track Ballast-Wheel Interaction Simulation
## 1 Introduction
Because the pieces of gravel can be separated and re-attached,conventional FE methods, which do not allow the separation of the elements, exhibit limitations regarding the modeling of gravel-filled ballast. To overcome this limitation, DEM-based modeling and simulation methods were investigated in this study. Using a DEM approach, the individual pieces of gravel can be modeled; hence, the interactions between the pieces of gravel in contact and between the gravel and other objects can be simulated. For a rational simulation of the ballast-wheel interaction, appropriate modeling and simulation strategies should be adopted considering the characteristics of the gravel used for the track ballast. To consider the interlocking of the gravel elements in contact, a clump-type rigid object is mainly used for each piece of gravel. Whereas the gravel pieces are modeled based on DEM, the other objects that contact and clash with the gravel layer are modeled based on FEM to calculate and consider the energy absorption of the deformable bodies. Thus, a DEM-FEM combined simulation method is adopted in this research. An experiment was conducted to examine the behavior of a freely dropped object that clashes with the gravel layer. To validate the simulation method, the motions of the dropped weight, obtained using both the experiment and the simulation, were directly compared. In addition, case studies were conducted to investigate the effects of the parameters of the gravel-gravel and gravel-object contact models on the simulation results for the ballast-wheel interaction.
###### Abstract  
The paucity of in-situ records, particularly in the glaciated mountainous region, is an obstacle in cryosphere ecology and environmental studies. Generally, available gauge station data is fragmented and covers valleys; thus, the use of gridded precipitation products (GPPs) is crucial in such complex terrains. However, these GPPs suffer from systematic biases and uncertainties owing to parameterization deficiencies. Therefore, the main goal of this research is to systematically evaluate the long-term performance and differences of the newly launched MSWEP in comparison to APHRO, CHIRPS, ERA-5, and PGMFD over the transboundary region of Indo-Pak (1981-2009) at spatial (whole to sub-basins) and temporal (daily to seasonal) scales. Findings reveal (1) overall, five GPPs produced well annual spatial precipitation variability with high magnitudes in the northwestern and low in the northeastern region. (2) The estimations from GPPs also divulged better correlation with in-situ observations (MSWEP = 0.86, APHRO = 0.76, ERA-5 = 0.81, CHIRPS = 0.57 and PGMFD = 0.68) at daily span. Better performance was observed during the monsoon compared to winter and pre-monsoon seasons. (3) Lately, estimates from MSWEP are more reliable for all the seasons, especially in the winter season, with the highest CC (0.90) and lowest relative bias (3.03%). (4) All GPPs (excluding ERA-5) overestimated light precipitation (0-1 mm/day) and underestimated moderate to heavy precipitation, in contrast to the ERA-5 that tended to underestimate the light but overestimate moderate (1-20 mm/day) and heavy precipitation (>20 mm/day) events. The CHIRPS was less accurate in detecting most of the precipitation events. The MSWEP product captured all precipitation intensities more accurately than other GPPs. The current research indicates considerable implications for product improvement and data users for choosing better alternative precipitation data at a local scale.  
GPPs; APHRO; CHIRPS; ERA-5; PGMFD; MSWEP; Indo-Pak Article
## 4 Simulation Analysis
### Parameter Settings  
For the reward function, the load weight is set to five, and the delay weight is set to one to effectively reduce satellite congestion. To avoid local optima, the \(\varepsilon-greedy\) strategy is used during pre-training with an initial \(\varepsilon\) of 0.8. To accelerate convergence, a decay factor of 0.998 is introduced, reducing \(\varepsilon\) after each iteration. To ensure network stability, the learning rate is set to 0.7 during Q-table Initialization and 0.3 during operational phase. The specific parameters are shown in Table 5.
# Review of the Research Progress in Combat Simulation Software
## 3 Simulation Engine and Simulation Framework
### Simulation Framework
#### 3.2.5 Comparison and Analysis  
From the perspective of developing distributed combat simulation systems, we selected four metrics (i.e., distributed ability, modularity, scalability, and generality) and performed a general comparison among the aforementioned four simulation frameworks. Here, _distributed ability_ represents the ability to support a simulation on distributed computers linked via a communicating network; _modularity_ measures how well the framework can be decomposed into smaller pieces with standardized interfaces; _scalability_ denotes how easy it is to grow or shrink the framework with respect to the simulation model, problem size, and secondary development; and _genetality_ describes the application's ability to be applied to other scenarios.  
As shown in Table 4, we marked a number of stars on the four selected metrics for each software. Since we could not obtain the FLAMES, AFSIM, and E-CARGO software, the results were evaluated according to the public information released by the relevant software developers. Our future work includes trying to obtain the software for experimentation and verification.  
\begin{table}
\begin{tabular}{l l l l l} \hline \hline
**Framework** & **Distributed Ability** & **Modularity** & **Scalability** & **Generality** \\ \hline FLAMES & \(\mathbf{\star\star\star\star\star}\) & \(\mathbf{\star\star\star\star\star}\) & \(\mathbf{\star\star\star\star\star}\) & \(\mathbf{\star\star\star\star}\) \\ XSIM & \(\mathbf{\star\star\star\star}\) & \(\mathbf{\star\star\star\star\star}\) & \(\mathbf{\star\star\star\star}\) & \(\mathbf{\star\star\star\star}\) \\ AFSIM & \(\mathbf{\star\star\star\star\star}\) & \(\mathbf{\star\star\star\star\star}\) & \(\mathbf{\star\star\star\star\star}\) & \(\mathbf{\star\star\star\star\star}\) \\ E-CARGO & \(\mathbf{\star\star\star\star}\) & \(\mathbf{\star\star\star\star\star}\) & \(\mathbf{\star\star\star\star\star\star}\) & \(\mathbf{\star\star\star\star\star\star}\) \\ \hline \hline \end{tabular}
\end{table}
Table 4: Comparison between the simulation frameworks.  
Figure 6: Component-based architecture.  
We observed the following based on the results listed in Table 4:  
* AFSIM and FLAMES have a very good distributed ability.
* Software modularization has become an important design principle in software engineering, and all four frameworks have good modularity.
* AFSIM and E-CARGO perform relatively better than the other two frameworks.
* E-CARGO outperforms the others in generality, since it can simulate complex problems in collaboration and complex systems.
# Methodology for Conceptual Navigational 3D Chart Assessment Based on Eye Tracking Measures
## 1 Introduction  
Maps unquestionably stand as one of the most important human inventions. For millennia, maps have allowed people to describe the Earth, travel the world, and return to places they have already been. During the 19 th century, nations with access to water areas and with a developed merchant navy established their own Hydrographic Offices, whose aim was to produce nautical charts and nautical publications [1]. Another progression, linked to the development of electronics and the digitalisation of paper resources, made it possible to develop electronic navigational charts (ENCs). Nowadays, the map content and the format of the navigation map itself are being standardised by the IHO (International Hydrographic Organisation). Its primary purpose is to be used with an Electronic Chart Display and Information System (ECDIS) to meet the International Maritime Organization (IMO) in the International Convention for Safety of Life at Sea [2] chart carriage requirements. The product specification is detailed in S-101 [3], provided and developed by the IHO.  
From paper charts, people have switched quite easily to electronic charts presented in the ECDIS systems, where it is possible not only to display the chart content but also to carry out simple analyses, such as route planning, observing the movement of other vessels in the area or determining the safety contour (isobath) [4]. Two important points about nautical charts, in particular, should be noted: firstly, nautical charts can only be understood with full knowledge and familiarity with navigational techniques; and secondly, nautical charts have always been primarily a navigational instrument rather than intended to represent the Earth [5].
## 2 Materials and Methods
### The Latest MeteoSwiss Dual-Polarization Weather Radar (RADAR) Network Data
#### 2.2.1 Relative and Absolute Calibration of the Ground-Based Radars  
In order to guarantee system stability and reproducibility, instrumental calibration of the radar using an internal microwave equipment must be implemented. In our approach at MeteoSwiss, internal calibration is continuous, automatic and done independently for both polarization channels. A reference power from a stable source is injected, and that value (\(\pm\) a given uncertainty) is read by the receiver. This concept for relative calibration does not require any signal from external active or passive sources. It has to compensate for variations of the radar equipment, and thus guarantees stable conditions for precipitation measurement. It is of particular importance after any maintenance, especially a corrective maintenance with component replacement. Hence, the parameter of relative calibration defines our ability to reproduce in the future the values we measure today. For the MeteoSwiss radars, relative calibration is performed continuously and automatically using a noise source [34] and an integrated test signal generator, as well as offline during preventive maintenance. The noise source signal is inserted every 2.5 min in both polarization channels of the receive path, both before the T/R limiter and at the entrance of the first stage of the low noise amplifiers.  
Absolute calibration of the whole radar refers to the electrical-electromagnetic tuning of the system versus some known reference targets (e.g., a metal sphere or other reflectors with known radar cross sections) at various ranges. This requires detailed knowledge of the whole system, including losses of the receiver and transmitter chains, antenna gain, random losses, noise factor, matched filter losses, and atmospheric attenuation. Apart from few experiments during the site acceptance tests using the armasuisse Time Stamp Amplitude equipment (TSAMP) and radar target simulator (RTS) [35], absolute calibration of both transmit and receive chains is not envisaged in the MeteoSwiss current generation network. Nevertheless, absolute calibration accuracy of the receive chains (vertical and horizontal polarization) is checked on demand, typically a few times per year, using the methodology presented in [36].