esa-sceva/satcom-chunk-collection huggingface dataset:
# A Hybrid Autoencoder Network for Unsupervised Image Clustering
## 4 Numerical Experiment
### Experiment Result
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Models**} & \multicolumn{3}{c}{**MNIST**} & \multicolumn{3}{c}{**CIFAR-10**} \\ \cline{2-7}  & **ACC** & **NMI** & **ARI** & **ACC** & **NMI** & **ARI** \\ \hline \(k\)-means & 0.7832 & 0.7775 & 0.7053 & 0.1981 & 0.0594 & 0.0301 \\ FCM & 0.2156 & 0.1239 & 0.0510 & 0.1702 & 0.0392 & 0.0256 \\ SC & 0.7128 & 0.7318 & 0.6218 & 0.1981 & 0.0472 & 0.0322 \\ LRR & 0.2107 & 0.1043 & 0.1003 & 0.1307 & 0.0430 & 0.0030 \\ LSR1 & 0.4042 & 0.3151 & 0.2135 & 0.1979 & 0.0605 & 0.0364 \\ LSR2 & 0.4143 & 0.3003 & 0.2000 & 0.1908 & 0.0637 & 0.0316 \\ SLRR & 0.2175 & 0.0757 & 0.5550 & 0.1309 & 0.0131 & 0.0094 \\ LSC-R & 0.5964 & 0.5668 & 0.4598 & 0.1839 & 0.0567 & 0.0258 \\ LSC-K & 0.7207 & 0.6988 & 0.6081 & 0.1929 & 0.0634 & 0.0389 \\ NMF & 0.4635 & 0.4358 & 0.3120 & 0.1968 & 0.0620 & 0.0321 \\ ZAC & 0.6000 & 0.6547 & 0.5407 & 0.0524 & 0.0036 & 0.0000 \\ DEC & 0.8365 & 0.7360 & 0.7010 & 0.1809 & 0.0456 & 0.0247 \\ CAE & 0.6809 & 0.6963 & 0.5666 & 0.2232 & 0.0870 & 0.0451 \\ AAE & 0.6217 & 0.5910 & 0.4351 & 0.1310 & 0.0204 & 0.0071 \\ \hline Hybrid Model 1 & **0.8367** & 0.8031 & 0.7490 & **0.2308** & 0.1002 & 0.0543 \\ Hybrid Model 2 & 0.8104 & **0.8085** & **0.7580** & 0.2217 & **0.1017** & **0.0573** \\ \hline \hline \end{tabular}
\end{table} 
Table 2: The performance comparison between various clustering methods. Figure 6: (**a**) Confusion matrix of MNIST; (**b**) Confusion matrix of CIFAR-10.
## 1 Introduction
[19] studied the influence of pre-existing cracks at different angles on the propagation of cracks in rocks using the Realistic Failure Process Analysis (RFPA) system for rock fracture analysis. [PERSON] et al. [20] proposed a hybrid finite-discrete element method to simulate rock fracture behavior under different loading rates and demonstrated the superiority of this approach. [PERSON] et al. [21] use the experimental analysis method and data collection method to study cloud computing-related technology and finite element method, rock tensile fracture, and numerical model. The researchers in [22; 23; 24] used the RFPA numerical analysis system to investigate the influence of intersecting cracks on the mechanical properties and deformation characteristics of rock under uniaxial compression and tension conditions. In summary, although experts and scholars have conducted a considerable amount of experimental and numerical simulation research on the evolution of damage and failure modes in pre-cracked rock specimens, many of these experiments have employed concrete or similar rock-like materials instead of actual rocks. However, such materials possess notable disparities in physical and mechanical properties compared to real rocks. Consequently, using them to simulate the failure process of pre-cracked rocks may lead to inaccurate conclusions regarding the influence of pre-existing cracks on rock behavior. To address this limitation, in this study, we chose fine-grained sandstone as the experimental material and conducted splitting tests on sandstone specimens with pre-existing cracks oriented at different angles. The entire process was monitored in real time using acoustic emission, and the influence of pre-existing cracks on the strength and failure characteristics of the specimens was analyzed. The energy evolution patterns of specimens with pre-existing cracks under five distinct working conditions during the failure process were calculated and analyzed. Furthermore, the relationship between maximum energy absorption and other rock parameters was examined. Energy, as an important parameter for representing rock fracture characteristics, has been widely used in dynamic rock fracture testing research [25; 26; 27; 28; 29]. Therefore, in this study, energy theory was also employed to elucidate the failure mechanism of pre-cracked rocks and analyze the correlation between energy and the failure of such rocks. These findings offer reference points and theoretical guidance for the analysis of rock mass structures and their stability in mining and tunnel excavation projects, as well as for the monitoring and prevention of engineering disasters.
# Management of Acute Life-Threatening Asthma Exacerbations in the Intensive Care Unit
## 4 Acute Life-Threatening Asthma Advanced Management in the ICU
### Heliox  
The primary components of atmospheric air are nitrogen (-78%) and oxygen (-21%). A mixture of helium (He) and oxygen (O\({}_{2}\)) (known colloquially as heliox) has been used to reduce airway resistance and thereby reduce the work of breathing. While having asimilar viscosity to nitrogen, helium has a higher thermal conductivity, and therefore, a helix gas mixture of 79% helium and 21% oxygen has a density almost six times lower than atmospheric air. Further, CO\({}_{2}\) diffusion and elimination appear to be increased since it diffuses four to five times faster through a mixture of He-O\({}_{2}\) than through N\({}_{2}\)-O\({}_{2}\). Finally, helium mixtures have been shown to mediate redistribution of gas throughout the lungs and produce an increase in alveolar ventilation through a reduction in CO\({}_{2}\) dead space, facilitated by a better diffusion of CO\({}_{2}\) in the low-density helium-oxygen mixture [137, 138].  
Helium mixtures were used as early as the 1930s in respiratory distress, since little else was available for the treatment of acute bronchospasm. It fell out of favour since supplies dwindled during World War II, and the subsequent invention of dedicated potent bronchodilators made it effectively obsolete for this purpose [137]. There are controversies over its use due to potentially consequently lower oxygen concentrations used in the gaseous mixture and due to its relatively complicated technical application and high costs. The flow meters and nebuliser generator systems used in ventilated patients must be adapted to use heliox [139]. A 2006 meta-analysis of ten trials containing 544 acute asthma patients studied the effect of heliox administration on pulmonary function tests for non-intubated acute asthma patients. Heliox only improved pulmonary function in a subgroup of patients with the most severe baseline impairment; however, this conclusion was based on a small number of studies. The analysis included trials from both adults and children, and there were no significant differences between these groups [140]. A further 2014 meta-analysis of 11 trials and 697 patients showed an overall statistically significant increase in mean peak expiratory flow. Furthermore, the effect was maximised in patients suffering the most severe asthma exacerbations [141]. There is ample evidence expounding the theoretical benefits of helium, with some small studies and meta-analyses showing clinical benefit; however, there do not exist any high-powered studies showing significant clinical benefit [138, 139, 142]. Again, similar to other ICU interventions, further studies are needed to evaluate the use of heliox in patients with acute asthma exacerbation in the ICU.
# Data-Aware Path Planning for Autonomous Vehicles Using Reinforcement Learning +
## 4 Experiments and Results  
In this section, we present the experiments conducted to evaluate the effectiveness of our proposed reinforcement learning-based approach to path planning for autonomous vehicles in urban environments. These experiments are crucial in demonstrating how our model addresses the dual challenges of optimizing driving time and ensuring timely data transfer. We aim to highlight the distinct advantages of our approach over conventional path planning methods that do not account for the complex interplay between traffic and bandwidth heterogeneity. To accomplish this, we conducted three experiments based on the simulation parameters illustrated in Figure 5. First, we assessed our reinforcement learning agent's performance against general baselines with varying reward functions. For this experiment, we investigated the performance of our agent with different start and end points to determine how effectively our approach manages trips of varying lengths. Next, we compared the performance of our trained agent when the data transfer requirement parameter is varied. Finally, we examined the impact of different map sizes on our agent's performance to evaluate the scalability of our solution.  
Figure 5: Simulation parameters.
###### Abstract
Accurate forecasting can help farmers, traders, investors, and policymakers make educated decisions, leading to efficient agricultural markets [10; 11], but the volatility presents enormous problems to them [3]. This study aims to systematically evaluate the application of ML, EL, DL, and time series techniques to agricultural commodity price prediction. This SLR intends to identify the used techniques in the commonly studied commodities of wheat, corn, and rice, along with their challenges and limitations, through analysis of original research articles. The goal is to provide a comprehensive understanding of the state of the field, highlight gaps in the literature, and propose directions for future research. The contributions of this study are as follows:1. This study provides a comprehensive analysis of common machine learning, ensemble learning, deep learning, and time series techniques used in agricultural commodity price prediction. 2. It offers insights into the unique prediction requirements of agricultural commodities forecasting. 3. This study investigates key challenges and limitations in agricultural price forecasting, including data availability, model interpretability, and computational complexity. This review focuses specifically on wheat, corn, and rice due to their status as the world's most important staple crops, as together, they provide more than half of the global dietary energy supply. These commodities are central to food security and widely traded and studied, making them an appropriate and impactful focus for a systematic review of forecasting methods.
# Satellite Network Task Deployment Method Based on SDN and ICN
## 2 Related Work  
### SDN and ICN Research on the Satellite Network  
As an emerging network management mode, the SDN can effectively improve the resource management level and the overall performance of the satellite network. The SDN separates the control plane from the forwarding plane, which can simplify the design and configuration of the satellite. The researchers introduced the idea of SDN into the satellite network to improve the efficiency of network management and configuration and designed a multilayer network structure based on the SDN integrated with the ground [10]. This includes the multilayer network structure and the deployment of virtualization services. To improve the management performance of the SDN in a satellite network, researchers have considered the dynamic configuration of the SDN controller to ensure the optimal controller position [11]. The SDN can obtain the global view of the entire satellite network and then combine it with the NVF technology to realize the effective arrangement and configuration of network resources. In [12], combining SDN and NVF technologies, an on-demand satellite network slicing framework was proposed to realize a flexible configuration of resources and various services.  
A satellite network is the supplement and extension of the ground communication network. Researchers try to integrate the ground network and satellite network to provide low latency and high-rate data delivery. For instance, in [4], the ground and satellite networks were integrated and the SDN technology was adopted to centralize and flexibly allocate spectrum resources. This confirms that the method based on the SDN provides obvious advantages in improving network throughput and reducing communication delay.  
The ICN also decouples content and communication addresses through a location-independent communication mode. The application of ICN technology to satellite networks effectively eliminates the impact of satellite dynamics on communication links. Especially for the collection of extensive Internet of Things data, the traditional IP address-based communication mode is inefficient. Researchers use both SDN and ICN technologies in the satellite networks to add the characteristics of the cache in the ICN network to the satellite network. This improves the delivery delay of the content [13]. To cope with the rapid growth of satellite-ground network requests, researchers have designed an ICN-based architecture. By adopting cooperative caching and coding caching methods, satellite network traffic is reduced, and content retrieval efficiency is improved [14].
# Federated Learning-Based Service Caching in Multi-Access Edge Computing System
## 1 Introduction
The cache replacement mechanism of SCFL also incorporates available resources into the service selection process, which further contributes to the reduction in system service latency. The main contributions of this study are as follows:  
* We propose a FL framework system enabling MEC servers to determine, independently, service caching. Specifically, each MEC server utilizes its user data locally rather than sharing it with others. In addition, using FL enables each MEC server to acquire data characteristics corresponding to the entire system. * We adopt the AAE for the distributed service caching problem. In particular, AAE efficiently extracts complicated distributions of distributed user data within the FL framework. The proposed method efficiently addresses the challenge of the dynamic nature of MEC systems by using both local and global knowledge. * We conduct extensive experiments to determine the effectiveness of the model. Experiments that use both simulated and real-world mobility data are examined across multiple scenarios. The service hit ratio and service delay are used as key metrics to evaluate the performance of the service caching framework. The experimental results show that the proposed model increases the service hit ratio from 1.25 to 5 times, while service latency is reduced by 15-50% compared to its counterparts. The remainder of this paper is organized as follows. Section 2 presents the recent studies on service caching in the MEC system. We then describe the system architecture in Section 3. Details of the SCFL framework are presented in Section 4. Section 5 presents the simulation results. Finally, Section 6 concludes the paper.
## 2 Literature Review
The results show that the average speed and volatility of speed are reduced in severe weather conditions such as fog, increasing safety [26; 27]. The third group of studies included studies that employed PVD. These studies compared various MOEs between situations with in-vehicle information and situations without in-vehicle information. [PERSON] et al. (2022) evaluated truck drivers' driving behavior using GPS data and an in-vehicle driver monitoring system [28]. [PERSON] et al. (2022) evaluated the impact of a motorcycle safety warning system (MSWS) using RFID data [29]. [PERSON] et al. (2021) examined PVD collected from the safety pilot model deployment (SPMD) program to analyze vehicle maneuvers, such as differences in speed and lateral/longitudinal differences in acceleration in CV environments [30]. [PERSON] et al. (2020) evaluated the impact of in-vehicle warning information based on TTC, TET, standard deviation in acceleration, jerk, and rate exceeding the speed limit, which were reproduced from the PVD [31]. [PERSON] et al. (2019) compared time to collision with disturbance (TTCD) with TTC, which were calculated from the PVD in CV environments to determine which surrogate safety measure (SSM) was better for explaining rear-collision crash potentials [32]. [PERSON] et al. (2019) analyzed CV-based in-vehicle data to evaluate intersection crash risk using the semiparametric geographically weighted Poisson regression (S-GWPR) model and random parameter (RP) Poisson model [33]. The proposed study herein differs from previous ones in several respects. Most previous studies used either simulated data with warning information or investigated PVD to compare situations with and without in-vehicle warning information. On the other hand, the research seeks to evaluate the effect of improving driving behavior before and after warning information is provided using PVD. Unlike previous studies, we employed the speed-spacing relationship to evaluate in-vehicle warning information. The speed-spacing relationship is one of the fundamental relationships that enables the visualization of traffic state progression. One can differentiate aggressive or conservative drivers from ordinary drivers. However, there were limitations to constructing a speed-spacing relationship even using PVD, due to the difficulty of extracting two consecutive vehicle trajectories. Given that the CV systems employed in this study are equipped with ADSs, we could obtain spacing information to establish the speed-spacing relationship.
# Cubesats Allow High Spatiotemporal Estimates of Satellite-Derived Bathymetry
## 1 Introduction
Planet Labs, Inc. ([[http://planet.com](http://planet.com)]([http://planet.com](http://planet.com))) has successfully built and launched 281 CubeSats since 2013 at various phases. Now (2019), it has more than 148 satellites in sun-synchronous orbit which image nearly all off the global land surface and coastal marine surfaces at 3-5-m resolution daily. As such they provide near real-time imagery to the private industry, academic domain, and governmental organizations. The satellites are the so-called CubeSats 3U--about the size of a wine box (\(10\to 10\to 30\) cm) carrying a four-band multispectral camera and power/downlinking equipment. Having small size and being built at lower costs, the CubeSats have the potential to overcome tradeoff? among high spatial and temporal resolution because of the multi-satellite constellation approach. This is linked to the mass production of the hardware and low launch costs using various platforms, driving to affordable solutions for commercial satellite companies as well as non-profit and research institutes. A drawback related to the image quality is that the multispectral imagery is acquired using inexpensive sensors at different batch productions with variable radiometric quality, consistency, and signal-to-noise ratio in comparison to the space agency-funded missions (Landsat and Sentinel series) and the commercial platforms (e.g., Marxan Technologies and WorldView satellites) [16]. So far, the CubeSat have limited use in the natural environment mainly due to image quality related to the user needs and the among satellites cross-sensor calibration approaches. In the seascape community, even if the constellation has great potential in transforming coastal remote sensing, few studies have come out so far [17; 18]. The objective of the current study is the first utilization of CubeSat imagery to calculate Satellite-derived Bathymetry for a selected site in Crete, Greece, using a plethora of single images from the same month. Implementing the selected images, we apply the empirical method by [PERSON] [9], which requires only in-situ depth soundings. Based on the best fitted training model, we proceed by applying low pass filters for the enhancement of radiometric anomalies at neighboring pixels, and the calculation of bathymetry for the depth zones according to the International Hydrographic Organization (IHO). The latter approach provides insights into the suitability of the CubeSats for spaceborne bathymetry and of the results to the requirements of the IHO for the inclusion of such products in the production line of navigation charts.
## 4 Experimental Results
### Analysis of Results
#### 4.4.1 Experiment 1: Traffic Situational Awareness
Thus, the road traffic flows continue to be large, with the evening peak ending at 22:00 (horizontal coordinate 88 in the figure). From Figure 6, we can also find that there is still a mismatch between some road traffic situation levels and traffic flow: when the traffic flow value reaches the maximum value of the current time period, the calculated road traffic situation does not reach the maximum value, but the result is low; when the traffic flow decreases, the road traffic situation is still on the high side. Actually, this is because this paper only uses a single indicator to calculate the road traffic trend, in which the parameters between road traffic trend and traffic flow may have some deviation, so these cases occur. Generally speaking, the road traffic situation values calculated in this paper and the trend of actual traffic flow are basically consistent.
## 3 Analysis of Reaching Solar Heat Flux of Lunar Relay Satellite  
### Analysis of External Heat Flux for Relay Satellites in Halo Orbit  
Based on the proposed analysis method, the reaching solar heat flux on relay satellites in Halo orbit and elliptic frozen orbit is calculated.  
The Halo orbit and elliptic frozen orbit are normal long-term orbits for relay satellite [24]. In these two cases, the attitude of the satellite is coincident. While the relay satellite performs tasks, the load, such as an antenna which is usually located on the +Z plane, may point to the explorer on the Moon or the ground station on Earth for communication, namely in the pointing attitude. Additionally, the satellite should yaw to ensure exposure of the solar arrays. Furthermore, while the load is not functioning, the satellite may point to the Sun to secure energy supplies. Because the attitude of relay satellites is varied and complex, to simplify the calculation process, this paper only considers the pointing attitude and ignores the change of attitude in one track. In fact, any attitude can be transformed from the nadir attitude by the proposed method. The pointing attitude in this paper is defined as follows: the +Z axis points to the subject on the Moon (explorer or south pole of the Moon), and the +Y vector is the cross product of the +Z vector and solar vector. The +X axis is determined according to the right-hand rule [24].  
An Earth-Moon L2 point Halo orbit is the mission orbit of Chang'e-4 relay satellite, and the orbit plane of the Halo orbit is a space curved face. First, translate the satellite into a regular hexahedron with a flat surface and establish a hexahedral model in TD software. Assuming each face of the model has an edge length of 1 m and all satellite surfaces share identical optical properties, both the absorptivity and emissivity are set to 1.  
Based on the three-axis Earth-pointing attitude, input the calculated yaw and pitch angles according to the computation method in Section 2 to configure the pointing attitude. Calculation results of the solar heat flux on different surfaces are shown in Figures 3 and 4.  
Figure 3: Results of the solar heat flux on \(\pm\)X plane.  
In this attitude, the +Y axis is perpendicular to the solar vector. Hence, the solar heat flux on \(\pm\)Y plane is 0. From Figures 3 and 4, it can be seen that the solar heat flux varies wildly. Unlike conventional orbits that operate within a single plane, the Halo orbit is a three-dimensional spatial trajectory, resulting in more complex variations in external heat flux. The orbital period of the Halo orbit is 30 days. Analysis results reveal that when the satellite maintains its pointing attitude throughout the orbital cycle, the illumination trends on the +X and \(-\)X surfaces follow identical patterns, differing only in their temporal phasing. The trends on the +Z and \(-\)Z surfaces also follow the same patterns.