esa-sceva/satcom-chunk-collection huggingface dataset:
# 5G-Based Smart Healthcare and Mobile Network Security: Combating Fake Base Stations
## 2 Background
### 5G System and 5G-Based Smart Healthcare Network  
The 5G system stands as a cutting-edge mobile network technology designed to offer a low latency, a high bandwidth, and extensive machine-type communication capabilities, catering to a plethora of IoT applications spanning from sensors and robots to medical equipment and wearable electronics. Comprising user equipment (UE), base stations, and a core network, the 5G network forms the foundation of this transformative technology [4].  
The UE, serving as a modem, stores a permanent identifier, known as the international mobile subscriber identity (IMSI), and a key essential for mutual authentication between users and the network. Meanwhile, the base station acts as the access point connecting the UE to the radio access network and, subsequently, to the internet. Finally, the core network, functioning as the mobile network's backbone, manages all administrative tasks and traffic routing [4].  
[PERSON], [PERSON], and [PERSON] [5] offer valuable insights into the architecture of 5G- and IoT-enabled smart healthcare networks, emphasizing key enabling technologies such as small cells and software-defined networks. Moreover, they propose a comprehensive taxonomy for 5G smart healthcare, identifying potential future research opportunities within the realm of IoT-based 5G smart healthcare.  
Trials of 5G-based smart healthcare networks have been conducted in Taiwanese hospitals, facilitating the deployment of 5G private networks to support medical robots and augmenting medical staff in the wards [6].
# Novel Methodology for Condition Monitoring of
## 3 Methodology
### Reduction of Features  
After carrying out the feature calculation, a dimensionality reduction stage, by means of LDA, is also included in the proposed condition monitoring methods. Such a dimensionality reduction, which is based on a linear transformation, allows us to obtain a visual representation of all the evaluated conditions in a 2D space. Therefore, the new extracted features in the 2D space retain the most significative and discriminative information of the original set of statistical features since the new extracted features are composed of a combination containing different weights from the original features. Thus, these non-useful or correlated features may have low weights, whereas the significative features will have greater weighting.
## 3 Materials and Methods
### Semantic Workflow of Proposed Model  
The proposed workflow for aircraft recognition is divided into three primary stages, as illustrated in Figure 2: the data preprocessing phase, the training phase, and the testing phase. In the data preprocessing phase, various techniques are applied to prepare the input dataset for training and testing. This contains procedures like grayscale picture conversion and average division standardization. Additionally, techniques for data augmentation are used to diversify the training dataset and reduce the danger of model overfitting. These augmentation techniques include horizontal flipping, rotation, zooming, shearing, width and height shifting, and picture rotation. The U-Net model is used as the fundamental architecture in the training phase, and this model is trained using the enhanced training dataset created in the preceding step. In order to evaluate the trained model's prediction accuracy and confirm the performance of the suggested model, test pictures are fed through the trained model in the testing phase. This stage acts as the last assessment of the model's capability to spot airplanes in satellite photos.  
In this study, the dataset is partitioned into three segments for training, validation, and testing. The training and validation portions of the dataset are utilized for training and validating the proposed model [41]. Subsequently, the trained model is employed to evaluate its performance using the testing dataset. It is worth noting that CNN-based approaches often require substantial computational resources. To expedite the computational processes within the neural network, the training and validation operations were conducted on a GPU utilizing NVIDIA CUDA technology. CUDA is a parallel computing technology that leverages numerous independent streams to accelerate operations. It is widely supported by modern NVIDIA graphics cards and is compatible across various platforms. Additional details about the dataset and the proposed model are provided in the subsequent sections.  
Figure 2: Semantic workflow of proposed aircraft recognition model.
## 2 Materials and Methods
### Equipment  
A Sensors & Software Inc. (Mississagua, ON, Canada) Noggin(r) GPR system having 250 MHz antennas (Figure 3a,c) was employed to detect buried drainage pipes. The antennas used were shielded and had a frequency range from 125 to 375 MHz, with a center frequency of 250 MHz. Previous research [3; 4; 5; 6; 7] indicated that 250 MHz center frequency antennas worked best for finding clay tile and CPT drainage pipes in agricultural settings. Integration of RTK/GNSS with the GPR system allowed accurate latitude and longitude coordinates to be obtained at field locations where potential drainage pipes were detected. In order to obtain RTK/GNSS coordinates at Sites 1 and 2, a Topcon Corporation (Itabashi, Japan) GNSS (Global Positioning System--GPS and Globalnaya Navigazionnaya Sputnikovaya Sistema--GLONASS) FC-200 rover receiver (Figure 3a) and Topcon Corporation GNSS (GPS and GLONASS) HiPer XT base station receiver (Figure 3b) were utilized. At Site 3, a Topcon Corporation GRS-1 dual-frequency, GNSS (GPS and GLONASS) rover receiver and Topcon Corporation PG-S1 hand-held controller were employed together (Figure 3c) with a virtual base station set-up through the Ohio Department of Transportation's (ODOT) network of Continuously Operating Reference Stations (CORS) [8]. Time domain reflectometry (TDR) soil water content values were collected using a Spectrum Technologies, Inc. (East Plainfield, Illinois) Field Scout TDR-300 with 20 cm waveguides (Figure 3d). The TDR water content measurements were utilized to determine soil dielectric constant values [9], that in turn were used to calculate preliminary soil radar velocities [10; 11], which were then employed to convert GPR two-way travel times to depth values.
# MonoMR: Synthesizing Pseudo-2.5D Mixed Reality Content from Monocular Videos
## 6 Applications
### Effective Surveillance System  
The existing surveillance systems display videos through a single display with divided windows or multiple displays. However, these methods are complex for a user to observe the plurality of screens simultaneously. Mainly, recognizing the place displayed on the monitor is not intuitive. In order to address this problem, a system [45] has been proposed where multiple camera images are synthesized into a single 360-degree image and displayed to a VR HMD. However, the entire scene cannot be recognized within a limited field of view of the HMD, and it's hard to recognize the depth of the target object.  
Constructing an efficient surveillance system with the MonoMR is possible because the proposed system can synthesize a single scene from several monocular cameras. We synthesized the four surveillance videos of CMUSRD [46] into a single scene using MonoMR as the demo application of the surveillance system (Figure 15c). The user can intuitively perceive a place where a specific target is located. In addition, even if the target moves from the camera viewpoint to another camera's viewpoint, the user can track the moving target intuitively. Since the system can synthesize content from various kinds of videos, there are many other potential applications besides the ones proposed.
# Evaluation of Novel Preformed Particle Gel System for Conformance Control in Mature Oil Reservoirs
## 1 Introduction
Among these, carboxymethyl cellulose (CMC), a modified cellulose, emerges as a noteworthy candidate with versatile applications across diverse industries including food, pharmaceuticals, water treatment, drilling muds, and many other fields [27; 28; 29; 30]. In the realm of materials science, the utilization of polysaccharides in various applications has been hindered by their inherent limitations compared to synthetic polymers. To overcome these constraints, chemical modifications have been strategically employed to enhance properties such as heat and abrasion resistance, mechanical strength, water or oil repellency, thermal stability, and antibacterial activity [31; 32; 33; 34]. An effective approach to impart novel attributes to these natural polymers involves the grafting of synthetic polymer chains onto their molecular backbones. The advancement of polysaccharide-based grafted materials has been a focal point of extensive research endeavors over the years [35; 36; 24; 37]. These materials, harnessed through three primary pathways known as the \"grafting through\" process, \"grafting onto\" process, and \"grafting from\" process, have demonstrated versatility in diverse applications. Their utility extends across various applications [38; 39; 40; 41; 42; 43; 44; 45; 46]. Despite the manifold applications of polysaccharide-based materials, only a limited number of studies have proposed PPGs constructed from these natural polymers. Notably, works by [PERSON] et al. [47] and [PERSON] et al. [48] utilized starch-grafted polyacrylamide loaded with nanosilica and alginate/polyacrylamideamide, respectively. [PERSON] et al. [49; 50] introduced PPGs based on chitosan. This study aims not to supplant existing polyacrylamide-based PPGs but to mitigate their environmental impact by incorporating CMC into their structure. Additionally, this research seeks to endow the prepared PPGs with enhanced characteristics. Addressing key parameters highlighted by [PERSON] et al. [51], such as particle size, swelling capacity in saline solutions, swollen particle strength, and thermal stability, the focus is on developing multi-sized PPGs based on natural polymers. These PPGs are envisaged to exhibit a high swelling ratio in high-saline media, augmented mechanical strength, and enhanced thermal stability at elevated temperatures, contributing to the advancement of environmentally sustainable and performance-optimized PPGs. In this paper, a systematic approach was followed to evaluate the performance of the newly developed CMC/PAMBA PPG under various conditions of salinity, pH, and temperature. Core flooding experiments were conducted to assess the plugging efficiency of this novel PPG system.
## 6 Conclusions  
In this paper, a two-stage DC/DC converter, buck and push-pull, was proposed. The proposed power converter was studied based on circuit analysis. In addition, a prototype was built, and the theoretical analysis was validated by the experimental results. The proposed two-stage converter enjoys the following advantages:  
(1) All parasitic parameters, including the leakage inductance, magnetizing inductance, and parasitic capacitance, are fully utilized in the proposed two-stage power converter. Only an external resonant capacitance is required for the resonant tank. Therefore, fewer components are needed.  
(2) In addition, all power switches, including the main switches and the rectifier diodes, operate under ZVS and ZCS. As a result, the switching loss is minimized, which contributes to the increase in the switching frequency and efficiency. Experimental results show that the efficiency can reach 94.5%.  
(3) Furthermore, the EMI issue is improved due to the soft switching advantages, which was validated by the experimental results.  
In conclusion, a two-stage power converter was proposed, where the first stage is a buck converter and the second stage is a resonant push-pull converter. The working principles and the calculations of the main parameters were researched. The theoretical analysis was validated by a prototype. The experimental results show that the proposed topology is suitable for high-voltage, high-efficiency applications.  
Conceptualization, W.Z., X.-B.S. and G.W.; methodology, W.Z., X.-B.S., G.W. and B.Z.; software, W.Z. and X.-W.H.; validation, W.Z., C.H. and B.Z.; formal analysis, W.Z.; investigation, W.Z. and B.Z; resources, W.Z. and C.H.; data curation, W.Z. and C.H.; writing--original draft preparation, W.Z.; writing--review and editing, B.Z., X.-B.S., G.W., X.-W.H. and B.G.; visualization, C.H.; supervision, W.Z.; project administration, W.Z.; funding acquisition, W.Z. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.
# User-Information-Aware D2D Multicast File Distribution Mechanism
## 7 Simulation Analysis
### Effects of Various Parameters on Performance of All Four Schemes
#### 7.3.1 Effects of Various Parameters on Utility
Therefore, the number of the D2D multicast receivers is far greater than the other three schemes, and it is easier to select a more suitable cluster head, resulting in a better utility value compared with the other three schemes. In other words, the efficiency of spectrum and energy are improved greatly. What's more, the robustness of the proposed scheme is also proved by comparing the performance of the proposed scheme under different parameter settings.
## 5 Results and Discussion
### [45\({}^{\circ}\)]\({}_{6}\) Model Calculation Results and Validation
#### 5.1.2 Matrix Damage  
When damage occurs at the interface, cracks are generated. The cracks extend into the titanium matrix, resulting in matrix damage, which corresponds to points b and c in Figure 15a under tensile stress. This result is also consistent with the acoustic emission experimental results in Figure 10a.  
Figure 17 shows that, when the torque reached \(-\)7194.46 Nm, matrix damage failure appeared from layer 6 and extended to layer 4, and the MDI of layer 6 was 1.014. This result shows that, when the torque reached \(-\)7322.29 Nm, all layers of the reinforced section started to exhibit different degrees of matrix damage. Additionally, the matrix damage trend extended from the failure initiation position to the ends of the model in Figures 17 and 18. The trend of the matrix damage was extended from the failure initiation position to both ends of the model, and the damage zone was gradually increased from  
Figure 15: Comparative analysis of the torsional strength calculation results and experiments: (a) [45\({}^{\circ}\)]\({}_{6}\) model; (b) [45\({}^{\circ}\)]\({}_{10}\) model.  
layer 1 to layer 6, with a 45\({}^{\circ}\) damage trend in the reinforced section of layers 1, 2, and 3. When the torque load reached \(-\)10,136.80 Nm, as shown in Figure 19, the 6 th-layer matrix was almost completely damaged. The matrix damage zone almost covered the U-shaped reinforced section of the model, and the damage zone was perpendicular to the axial direction, exhibiting a 90\({}^{\circ}\) damage trend. This result is consistent with the angle of the electron microscope experiment results in Figure 9b.  
Figure 17: MDI of a matrix of the [45\({}^{\circ}\)]\({}_{6}\) model under different loads.
# Deformation Behavior of Saturated Soft Clay under Cyclic Loading with Principal Stress Rotation
## 3 Test Procedure  
First, the sample was slowly pushed out from the thin-walled tube with a special pusher and then cut to the desired size (100 mm in outer diameter, 60 mm in inner diameter, and 200 mm in height) using a standard sample cutter. The soil cutter, cutting pedestal, and hollow cylindrical soil sample are shown in Figure 3. For detailed sample preparation principles and steps, refer to [PERSON] et al. [32]. The specimen was then installed on the base of the DHCA. After the sample was installed, the test steps were loaded. At the beginning of the tests, the saturation phase with a 300 kPa back pressure and 20 kPa effective confining pressure on each specimen lasted for 24 h and was then followed by the B-check [1]. If B > 0.97, the specimen would then be consolidated at an effective confining pressure of 100 kPa for approximately 48 h, and the main consolidation would be considered complete when the change in the volume of specimen is less than 100 mm\({}^{3}\) per hour. After that, under undrained conditions, the inner and outer confining pressure was kept constant, and the specimen was subjected to a cyclic loading with self-defined waveforms in axial force and torque. The loading waveforms are shown in Figure 4.  
In order to distinguish the effect of cyclic stress level and different principal stress rotations, two indexes, the vertical cyclic stress ratio VCSR and the torsional cyclic stress ratio \(\eta\), were used for definition, both of which are defined as follows:  
\[\text{VCSR}= \frac{\sigma_{\text{z}}^{\text{cyc}}}{2p_{o}^{r}} \tag{1}\] \[\eta= \frac{\tau_{\text{z}}^{\text{cyc}}}{\sigma_{\text{z}}^{\text{cyc }}} \tag{2}\]  
where \(\sigma_{\text{z}}^{\text{cyc}}\) and \(\tau_{\text{z}\text{z}}^{\text{cyc}}\) are the cyclic axial stress amplitude and the cyclic torsional shear stress amplitude, respectively, and \(p_{o}^{r}\) is the initial mean principal stress. The increase in the torsional cyclic stress ratio \(\eta\) indicates the increase in the principal stress axes rotation. If \(\eta\) = 0.00, it is actually a cyclic triaxial test.  
The test program is detailed in Table 3. Nine cyclic torsional shear tests were carried out at different values of VCSR and \(\eta\). All tests were carried out with a loading frequency of 0.1 Hz and loaded up to 1000 cycles, with 50 data points recorded per cycle.  
\begin{table}
\begin{tabular}{c c c} \hline \hline  & **Stress** & **Strain** \\ \hline Vertical & \(\sigma_{z}=\frac{W}{\pi\left(\frac{r_{o}-r_{o}^{2}}{r_{o}^{2}}\right)}+\frac{ p_{o}r_{o}^{2}-p_{o}^{2}}{\left(r_{o}^{2}-r_{o}^{2}\right)}\) & \(\varepsilon_{z}=\frac{z}{H}\) \\ Circumferential & \(\sigma_{r}=\frac{p_{o}r_
## 2 Materials and Methods
### Microseismic Monitoring Signals
#### 2.1.1 Microseismic Monitoring Data  
Microseismic monitoring data exhibit unique characteristics that are vital for effective event recognition and classification [26]. Firstly, these data demonstrate variations in signal intensity over both time and space, which may be attributed to complex changes in underground rock formations and mining activities. Second, mechanical processes, equipment breakdowns, subsurface water movement, or environmental conditions can contribute to high levels of noise in microseismic data. This complicates data processing because a good distinction between signals and noise is required. Furthermore, due to geological effects, the waveforms of microseismic data are frequently complex and diverse, reflecting the physical qualities of rocks and differences in subsurface structures. Finally, microseismic data span a wide range of frequencies and energy levels, implying that MS can manifest in a variety of frequency ranges and energy levels. This variability causes difficulties in event recognition and classification, necessitating the investigation and processing of various features.  
These microseismic surveillance data characteristics represent the complexity of the underlying rocks and mining activities, which require advanced data analysis techniques for interpretation and understanding. Variations in signal intensity across time and place suggest that the distribution of microseismic events is nonuniform, which may be related to the nonuniformity of underground rock layers or mining activity. To improve the detection and analysis of microseismic events in the presence of high noise levels, preprocessing measures such as blurring and filtering are required. The complex waveforms may reflect a variety of subsurface structures, which is important for recognizing various types of occurrences such as rock bursts, demolition, and microfractures. Because of the variety of frequencies and energy levels, multiscale and multifeature analysis approaches must be used to capture the many properties of microseismic signals.  
Understanding these properties of microseismic monitoring data is therefore critical for accurate identification and classification of microseismic occurrences. When confronted with such complicated data, researchers must devise proper data processing and analysis methods to distinguish between important events and irrelevant noise, as well as extract key information about microseismic events. Furthermore, different types of microseismic events may necessitate alternative feature extraction and classification approaches to ensure accuracy and reliability. These data features enable in-depth investigations of subterranean engineering and rock behavior and provide critical information for mining activities and underground engineering projects.
# A Review of Worldwide Strategies for Promoting High-Temperature Heat Pumps
## 4 The Promotion of IHPs over the World
### Eu  
A variety of directives such as the Energy Performance of Buildings Directive (EPBD), the revised Renewable Energy Directive (RED), and the Energy Efficiency Directive (EED) aim to promote HPs in the EU, particularly for domestic use [93; 94]. In particular, the EPBD requires Member States to develop long-term energy renovation strategies for buildings, aiming for an 80% to 95% reduction in CO\({}_{2}\) emissions by 2050, with HPs identified as a high-efficiency alternative to fossil fuel-based heating systems. It is supported in its purpose by the revised RED that highlights HPs as crucial for renewable heating and cooling, utilizing sources like ambient and geothermal energy and facilitating waste heat use from sectors including data centers [93; 94]. The EED states that when calculating the share of renewable energy within a district heating system, all heat provided to the network by HPs qualifies as renewable energy, and it also establishes that the evaluation of waste heat utilization must consider HPs together with other heat-to-power technologies [95]. The revision of the Energy Taxation Directive, on the other hand, aims to make HPs more attractive from a taxation perspective by reducing the difference between electricity and gas, reducing the VAT for energy-efficient technology, and taxing fossil fuels [96]. Other tools, like the Next Generation EU and REpowerEU, collectively support HP implementation in households, by providing funds to support a greener economy after the COVID19 pandemic and by boosting the annual sales of HPs, respectively [97; 98]. The European Commission has scheduled its Heat Pump Action Plan (HPAP) to release after the EU elections in June 2024. The HPAP aims to accelerate HP market adoption, outlining actions such as partnerships, communication, skills development, legislation, and financing. The Heat Pump Accelerator, involving industry, governments, and non-governmental organizations (NGOs), proposes solutions to HP sector challenges, including regulations to mandate HP use in industrial processes and prohibit fossil fuel-based solutions for industrial heat up to 200 \({}^{\circ}\)C [99; 99]. For the industrial sector, the Net-Zero Industry Act wants to amplify clean technologies' production in the EU by attracting investments and simplifying the regulatory framework, and, together with the Green Deal Industrial Plan that aims to accelerate the deployment of innovative and sustainable technologies, it represents a pillar for decarbonizing EU industry and encouraging the transition to HPs [100; 101].