esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Experimental TES System: Design, Construction, and Performance Evaluation of a Prototype
### Experimental Results and Discussion  
More than thirty charges and discharges have been performed on the lab scale prototype. During tests, no degradation of the system's performance was observed. Figure 6 describes the results for a storage phase. The tank was set in the vertical position and the HTF flowed from the top to the bottom of the tank. The HTF was heated at a constant rate up to a temperature at which it was then maintained afterwards. The temperatures are presented for an experiment performed at a heating rate of 2 \({}^{\circ}\)C/h, a final temperature of 64.6 \({}^{\circ}\)C and a volume flow rate of 100 L/h. This highlights that the temperatures in the cylindrical tank were symmetrical and independent of the radius (Figure 6a). Furthermore, as illustrated in Figure 6b, the storage prototype worked perfectly as a piston-type system i.e., the temperature was constant on a section perpendicular to the fluid flow.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Material** & **Thickness (m)** & **Outer Diameter (m)** & **Length (m)** \\ \hline Tank & 0.004 & 0.4 & 0.8 \\ Nodules & 0.002 & 0.098 & na \\ Insulation & 0.05 & na & na \\ \hline \hline \end{tabular}
\end{table}
Table 4: System geometry.  
Figure 6: Evolution of temperatures vs. time for a charge between 42.3 \({}^{\circ}\)C and 64.6 \({}^{\circ}\)C at 100 L/h. (**a**) Horizontal temperature variation, (**b**) vertical temperature variation.  
The outlet temperature of the tank started to increase almost 2 h after the inlet temperature had increased, which corresponds to the time it takes for the HTF to cross the tank. The stored heat was mainly in the form of sensible heat up until -8h. After that, the phase change of the SA-PA mixture began, resulting in the change in slope of the temperature curves in the tank due to the latent heat. This is particularly visible in the curves recorded in the bottom of the tank. When all the PCM mixture had melted, the storage became sensible again (liquid phase) and the outlet temperature quickly reached its final value (lower than the inlet because of the prototype's thermal losses). A similar behavior was observed during the discharge (cooling mode--see Figure 8). In both figures, the change in slope is not very large because the value of the latent heat of the PCM was quite low versus the sensible heat. This is due to the small volume of PCM that was inside the tank. The main reason is the instrumentation inside the tank, which severely reduce the space available for nodules.
# Smart Grid Protection, Automation and Control: Challenges and Opportunities
## 3 Evolution of Substation Architectures and Digital Modernizations for Smart Substations
### Comparasion of a Conventional P&C Systems vs. CPAC Approach
Each device requires constant care, making management more difficult and affecting the system's efficiency. In the last decade, CPAC solutions have emerged to make hardware in substations simpler. These integrated solutions combine several functions in a single system, reducing the complexity and enhancing the efficiency of the maintenance activities, but in different brands, functionalities are quite different, and this is an essential aspect during the selection of the best solution  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Criteria** & **Centralized Architecture with Communication Redundancy** & **Hybrid Architecture with Numerical Protection Relays** & **Hybrid Architecture with Numerical Protection Relays Using Simplified Local Protection** \\ \hline Main feature & Fully centralized protection system with PRP-based communications redundancy using Merging Units (MU) and CPAC systems to send and receive data over independent LAN networks. & Protection system with numerical protection relays capable of handling the Sampled Analogue Values (SAV) communication profile of IEC 61850-9-2, enabling them to function as merging units and provide information to the CPAC unit. & Protection system with numerical protection relays in the individual busy that communicate with the centralized CPAC unit via an Ethernet switch. This setup allows simplified local protection within the days and advanced substation-level protection within the CPAC unit. & Protection system with  
for each substation. For example, some of the equipment from the most important brands is described in Table 3. At the time of writing, equipment from major manufacturers such as GE [28; 29], Schneider Electric [30], and Ingeteam [31] does not offer compact devices with the functionalities presented by the ABB's SSC600. These manufacturers still maintain a protection and control devices categorization depending on a certain fault, rather than assembling all functionalities in one device unit. These solutions in functionalities are only comparable with SIPROTEC 7 SX85 [32], the SEL-487E [33; 34; 35], and the SSC600 [36; 37; 20; 38]. Another distinct feature of the ABB SSC600 is its centralized approach, housing all protection and control functions in one device. This not only simplifies the system architecture, but also reduces complexity.
## 2 Materials and Methods
### Model Application
#### 2.2.2 Soil Parameters  
Soil data were determined through field and laboratory measurements. Field measurements were carried out following the Beerkan Estimation of Soil Transfer parameters (BEST) method [47]. This method allows to estimate soil hydraulic properties from basic soil properties together with infiltration measurements. Disturbed soil samples were collected in order to determine the particle size distribution performed by sieving for sand fraction for each soil. For the analysis of the finer part, an automated particle size distribution instrument (METER Group, Munchen, Germany) was used. Sand, silt, and clay contents together with soil texture were identified according to the USDA (United States Department of Agriculture) system of soil classification. The topsoil of the Bonis catchment was classified, according to the different fractions of sand, clay, and loam, and Loamy fine sand for the majority of sampling locations, while others were characterized by a fine sand soil. For this study the average of the measured soil parameters was considered as representative for the entire catchment.  
Measured soil parameters at different land uses of the catchment were used as a first estimate to be subsequently calibrated. These parameters were also used to assess the contribution of each land use to hydrological response of the basin. The sampling points were selected as representative of the mainland uses of the basin. In order to simplify the data collection, similar land uses were gathered under the same land use category. This procedure generated a second simplified classification with 9 different land use classes instead of 16 as reported in the Table 1.
# High-Density 3D Printable Chipless RFID Tag with Structure of Passive Slot Rings
## 3 Design and Fabrication of 12-bit Chipless Tag Printed on F4 BM Substrate
The tag ID11111111111 is used as the reference tag for the evaluation of the corresponding states of the other tags. If the measured tag has the notch on the same position of the reference tag, it is labeled as the logic state \"1.\" On the contrary, if the measured tag has not the notch on the same position of the reference tag, it is the logic state \"0.\"  
Figure 13b-e indicate the result of simulation and measurement for the other coding tags. The frequency points of the logic '1' and logic '0' are in accordance to the reference tag ID(111111111111) of Figure 6. It is worth noting that results of simulation and measurement have obvious deviation at the high-frequency-range because of the geometry error on the printing of the smaller slot rings. However, the feasibility of our design can be verified. In practical application, UWB disc monopole antenna [20; 36] and CPW-fed quasi-circular monopole antenna [37] are used as the reader antennas. Figure 13: RCS magnitude for twelve Rectangular Slot Rings with (**a**) ID 1111111111 (**b**) ID 10101010101010 (**c**) ID 000000111111 (**d**) ID 010101010101 (**e**) ID 0100000010. Figure 14 shows the statistic results of the measured errors corresponding to the twelve rectangular slot rings. The minimum error is 0.02 GHz and the maximum is 0.6 GHz. It can be seen that the measurement errors are increased gradually with the resonant frequency increasing. On the one hand, the minimum side length of the rectangular slot resonant ring corresponds with the maximum error. The deviation of the resonant frequency is increased rapidly although there is only slight change in the dimension. On the other hand, according to Equation (1), compared with longer side, the shorter side of the rectangular slot ring corresponds to larger variation of resonance frequency. On the sense, precise fabrication is necessary in future industrial fabrication if high accuracy of resonant frequency is required in RFID identification system.
# Unmanned Autonomous Intelligent System in 6G Non-Terrestrial Network
## 4 Application of UAV-Aided Non-Terrestrial Networks in UAIS
### Unmanned Maritime Vehicles in UAV-Aided NTN Communication
#### 4.3.1 Unmanned Surface Vessels in NTN Communication
Therefore, a communication scheme based on ad-hoc network architecture with node position information for UAV-USV communication was investigated. Researchers of [167] proposed a self-adapted synchronized event-triggered formation control strategy aimed at decreasing communication burden. A formation control method for under-actuated USVs was studied using dynamic surface control. Inspired by the event-triggered mechanism, the authors of [168] also proposed a formation control scheme utilizing sliding mode control protocols within a fixed time. By employing the dynamic event-triggered approach, the system updated the controller status less frequently, thereby reducing the consumption of communication resources  
**Cooperative task coordination:** In cooperative tasks such as maritime rescue, surveillance, and harbor security, the UAV-USV cooperative mechanism heavily relies on reliable communications between them. A variety of studies have focused on the challenges of communication during UAV-USV cooperative operation since the oceanic environments have major impact on the communication system due to adverse weather and challenging channel conditions. The end-to-end delay, network throughput, and packet loss probability should be carefully optimized [169; 170]. The authors of reference [169] introduced a communication framework between UAVs and USVs for time-critical applications. According to previous research [171; 172], the communication range of UAV significantly affects the cooperation efficiency of the UAV-USV system. The authors of reference [173] proposed a UAV-USV cooperative perception scheme for coastal monitoring utilizing UAV-UGV cooperative platforms as communication relays. Additionally, a joint object detection algorithm was proposed using an enhanced CenterNet model. For UAV-USV cooperation, mobile edge computing schemes have also been applied to the maritime Internet of Things (MIoT) [174].
# Distinction Between Interturn Short-Circuit Faults and Unbalanced Load in Transformers
## 3 Materials and Methods
### Application of Fault Detection Techniques  
For all four experiments, the primary current waveforms were acquired as three vectors. These three signals were then processed using the Clarke transform to obtain the oscillation of the mean value of the ISP, which results in a single vector or discrete time signal [16]. This vector depends on the values of the three sinusoidal current signals; when the signals are balanced, the mean value of the ISP is a direct current component located at the maximum value of the three current signals. When the three-phase signals are unbalanced, the mean value of the ISP oscillates at a frequency of \(2f\), centered on a direct current component determined by the degree of imbalance present. The mean value of the ISP was analyzed using the FFT to obtain the frequency spectrum of the ISP mean value signal, thus moving from a time signal to the frequency domain, where the healthy transformer would ideally show a spectrum with only the direct current component at the zero component, but, in the case of imbalance, the \(2f\) frequency appears. For the analyses in this work, this frequency was expected for both imbalance and the incipient short-circuit faults analyzed. In this way, differences were identified in the frequency components and magnitudes for each experiment--imbalance and short circuits--compared to the behavior of the healthy transformer. The combination of these concepts serves as a fault detection tool [17; 18].  
On the other hand, it is possible to take advantage of the fact that, in a turn-to-turn short circuit, the current flowing through the shorted turns creates a low-impedance loop that causes heating in those turns due to the Joule effect. This results in a progressive and localized temperature increase in the fault area. In contrast, during an imbalance, the current remains within nominal thermal limits, resulting in a stable temperature profile over time [10]. Thus, when an increase in the \(2f\) frequency component is detected, the transformer is observed using an infrared image, which shows a stable temperature over time for an imbalance and an increasing temperature for an incipient short circuit, with a rate of increase that depends on the severity of the fault.
###### Abstract
In comparison to regular alloys, AMMCs have very good mechanical properties and are easier to mould and fabricate into any shape or size. Increased strength, improved fatigue resistance, high corrosion resistance, high warmth resistance, and higher wear resistance are some of the crucial properties that composite materials possess [10]. According to the literature, adding reinforcements improves a variety of mechanical properties, including ultimate tensile strength [11; 12; 13; 14; 15], wear resistance, microhardness, elongation, etc. The ceramic particles that are evenly distributed throughout the fine-grain matrix of metal matrix composites are the reason for the improved mechanical properties [16; 17; 18]. These aluminium metal matrix composites are widely used in high-tech structural and functional applications, such as in the aircraft, mineral, defence, automobile, thermal management, marine, transportation, automotive, and sports and recreation areas [19; 20; 21]. Metal matrix composites (MMCs) are manufactured using a variety of manufacturing processes. Stirring casting, powder metallurgy, squeezing casting, in situ processes, deposition techniques, and electroplating are part of the manufacturing process used in the manufacture of AMMCs [22]. MMCs that use friction stir processing (FSP) have a distinct advantage over MMCs that use other manufacturing techniques. When opposed to most other strategies, FSP has several distinct benefits. FSP is a special processing method that was developed from friction stir welding (FSW) [23]. FSP is a solid-state method that improves the mechanical properties of the base material by homogenization, microstructural, and particle refinement [24]. FSP has been demonstrated to have a short route, homogeneity, accurate microstructure, and densification. FSP's benefits include a finer grain, processing zone homogeneity, densification, and the homogenization of the aluminium alloy and composite precipitates [25]. To develop a metal matrix composite using FSP, a groove or hole is formed in the base material and reinforcement particles are dispersed using a tool [23]. Numerous works have demonstrated that marine grades of aluminium can be reinforced with different reinforcements using FSP techniques. Al\({}_{2}\)O\({}_{3}\)[26; 27; 28], TiC [27; 28], TiO\({}_{2}\)[28; 29], Al\({}_{3}\)Ni [30], B\({}_{4}\)C [31], SiC [32; 33; 34; 35], are some of the reinforcements used to fabricate MMCS and some of the works developed with the different reinforcements will be discussed in detail in the following sections. The literature has demonstrated that using various reinforcements in combination with the same base metal can result in different metal matrix composites with distinct properties. This review reports and compares the dominant base material from the marine-grade 5 xxx series and reinforcements used in the fabrication of aluminium metal matrix composites suitable for marine grades produced using friction stir processing.
## 5 Conclusions  
The FUI is an optical parameter that results from the interactions between solar radiation and components in water, and is significantly related to water quality. Thus, the FUI can be applied to evaluate water quality in the long term and at large scales. The accuracy evaluation indicates that the FUI can be successfully applied to Sentinel-2 data.  
Overall, Sentinel-2 can be used to carry out spatial distribution and seasonal and inter-annual variations. In addition, monitoring water quality is economical, efficient, and intuitive by remote sensing, and provides guidance for developing suitable management policies.  
Of the 41 lakes and reservoirs analyzed in Shenzhen and Guangzhou, 36% exhibited deteriorating water quality trends. Owing to the relatively scattered distribution of these lakes and reservoirs, relevant governance policies such as \"one lake, one policy\" can be formulated based on the actual scenario in each location. For example, weeds and debris can be removed regularly, aquatic organisms can be introduced to improve the self-purification capacity of the water body, and the discharge of pollutants and sub-standard wastewater can be reduced.  
In the future, we plan to apply the FUI to multi-source optical data to analyze the spatio-temporal variations on a larger scale, for a longer period, and for smaller water bodies. We also plan to collect more satellite-ground synchronous in situ data to evaluate the accuracy of the FUI.  
[PERSON] contributed to the conception and design of the study acquisition. [PERSON] contributed to the data analysis and main manuscript text. [PERSON] supervised the manuscript. [PERSON] validated the manuscript. All authors have read and agreed to the published version of the manuscript.  
This study was supported by the National Key Research and Development Program of China (2021 YFF0703900), the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA19030301), the Fundamental Research Foundation of Shenzhen Science and Technology Program (KCXFZ202002011006298; KCXFZ20201221173613035), the Fundamental Research Foundation of Shenzhen Technology and Innovation Council (Key Program) (JCYJ20200109115637548), the Fundamental Research Foundation of Shenzhen Technology and Innovation Council (General Program) (JCYJ20190806170814498), and the Fundamental Research Foundation of Shenzhen Technology and Innovation Council (JSCG2019112911427080).  
**Institutional Review Board Statement:** Not applicable.
# Development of a Digital System for Monitoring Emergency Conditions in 20 kV Distribution Networks
## 3 Results
### Development of a Measurement Node
To eliminate this issue, a detector is used to average the root mean square (RMS) value of the induced voltage, creating a constant voltage across a capacitor that changes in accordance with the sensor's voltage fluctuations. The level of this voltage is measured by a digital voltmeter, and the results are processed by an integrated microprocessor following a predetermined algorithm. This method allows for accurate detection of a sharp voltage increase during phase-to-ground faults.
## 3 The Epsom-Hyb Estimator
### Local Approximation Using a Taylor Expansion  
We revisit Equation (2) and consider the following piecewise quadratic approximation to \(\Psi\),  
\[\Psi(u)\approx\sum_{k}\Big{[}\Psi(u_{k})+(u-u_{k})^{\prime}\
abla\Psi(u_{k})+ \frac{1}{2}(u-u_{k})^{\prime}\
abla^{2}\Psi(u_{k})(u-u_{k})\Big{]}\mathbb{1}_{A _{k}}(u), \tag{5}\]  
where \(u_{k}\) is a representative point of \(A_{k}\). This improves upon the initial idea of the piecewise constant approximation in the hybrid methodology by introducing a second-order Taylor approximation. By introducing higher-order terms, we trade the convenient simplification of the integral in Equation (3) for increased local accuracy of the approximation. Uponexponentiating the approximation in Equation (5), we observe that the second exponential in the summation below is proportional to a Gaussian density,  
\[e^{-\bar{\Psi}(u)}=\sum_{k}\exp\Big{\{}-\Psi(u_{k})+u_{k}^{\prime}\lambda_{k}- \tfrac{1}{2}u_{k}^{\prime}H_{k}u_{k}\Big{\}}\exp\Big{\{}-\tfrac{1}{2}u^{\prime} H_{k}u+(H_{k}u_{k}-\lambda_{k})^{\prime}u\Big{\}}\mathbb{1}_{A_{k}}(u),\]  
where \(\lambda_{k}:=\
abla\Psi(u_{k})\) and \(H_{k}:=\
abla^{2}\Psi(u_{k})\) represent the gradient vector and the Hessian matrix of \(\Psi\) evaluated at \(u_{k}\), respectively. Since \(\gamma\) is log-concave, the Hessian matrix is positive definite, and hence invertible. Integrating the exponential above, we arrive at the following approximation to \(\mathcal{Z}\):  
\[\int_{A}e^{-\Psi(u)}du\approx\int_{A}e^{-\bar{\Psi}(u)}du=\sum_{k}C_{k}\int_{A _{k}}\mathcal{N}\Big{(}u\mid H_{k}^{-1}b_{k},H_{k}^{-1}\Big{)}du=:\widehat{ \mathcal{Z}}_{\text{EPSOM}-\text{Hyb}}. \tag{6}\]  
Here, \(C_{k}=\exp\bigl{(}-\Psi(u_{k})+\lambda_{k}^{\prime}u_{k}-0.5u_{k}^{\prime}H_{ k}u_{k}+0.5m_{k}^{\prime}H_{k}m_{k}\bigr{)}\), \(b_{k}=H_{k}u_{k}-\lambda_{k}\), and \(m_{k}=H_{k}^{-1}b_{k}\). Before \(\widehat{\mathcal{Z}}_{\text{EPSOM}-\text{Hyb}}\) can serve as a viable estimator for \(\mathcal{Z}\), we must address the remaining questions of how to determine the value of each \(u_{k}\in A_{k}\) and how to compute the intractable Gaussian integrals in Equation (6). In the next two sections, we provide scalable methods to accomplish these tasks. It is worth noting that the original hybrid estimator does not face the same intractability issue due to the simplistic nature of the constant approximation used in Equation (3). Our incorporation of higher-order terms complicates the subsequent calculation, which necessitates a scalable algorithm like EP to compute the truncated Gaussian integrals.
# A Modified Bio-Inspired Optimizer with Capsule Network for Diagnosis of Alzheimer Disease
## 3 Methodology
### Description of Datasets  
The proposed fuzzy-based superpixel-clustering algorithm and the MGTO-CapsNet model performance was tested on the ADNI, real time, and AIBL datasets. The ADNI dataset comprises 1662 sMRI images; here, the individuals are categorized into three types, including normal control (NC), AD, and mild cognitive impairment (MCI) [35]. The goal of ADNI is to create biochemical, genetic, imaging, and clinical biomarkers for the early identification and monitoring of AD. The historic public-private cooperation, which was established more than ten years ago, has significantly advanced AD research by facilitating the exchange of data amongst researchers worldwide ([[https://adni.loni.usc.edu/data-samples/](https://adni.loni.usc.edu/data-samples/)]([https://adni.loni.usc.edu/data-samples/](https://adni.loni.usc.edu/data-samples/))) accessed on 14 November 2023. Furthermore, the AIBL dataset ([[https://aibl.csiro.au](https://aibl.csiro.au)]([https://aibl.csiro.au](https://aibl.csiro.au))) accessed on 21 November 2023 consists of 496 sMRI images, and the individuals are categorized into three types, including 17 progressive MCI (pMCI), 93 stable MCI (sMCI), and 307 NC [36] subjects. Additionally, the real-time dataset was acquired from Rajiv Gandhi Government General Hospital (Chennai), and it comprises 200 sMRI images belonging to three classes (NC, AD, and MCI). The acquired sample sMRI images from the ADNI dataset (a), including the real-time dataset (b), and AIBL dataset (c) are visually presented in Figure 2.