esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction
That approach is different from the traditional dual-satellite integrated navigation algorithm in that it can complete accurate real-time navigation and positioning without the aid of an altimeter and continuous observation, however, in this algorithm, when the switching time is relatively large, the positioning error may deteriorate, especially when switching is based on the same orbit. Reference [21] proposed a combined navigation and positioning algorithm based on the relative motion information measured by the INS, the position information of the two satellites and the pseudorange information at multiple times under the scenario of only 2 visible satellites; this algorithm can ensure stable, reliable navigation and positioning results, similarly, the algorithm also needs to observe through continuous position information. Our article makes full use of the many advantages of the LEO constellation, and considers using it as a tentative study of a navigation and positioning scheme for the whole system rather than an augmented system. When only two visible LEO satellites are available, the proposed algorithm can effectively complete the precise navigation and positioning service by alternately switching, and combining with the altimeter under the establishment of a reasonable elevation measurement model. In Section 2 of the article, on the basis of the principle of altimeter height measurement, based on the concept of similar ellipsoids, the observations related to user elevation are established, and derivation is carried out we then describe the basic principle and process of the algorithm in detail. In Section 3, we established the state equations and measurement equations of the entire system. In Section 4, by setting the simulation conditions and parameters reasonably, simulation experiments were performed on different scenarios and the qualitative and quantitative analysis results were given; at the same time, our algorithm was compared with other typical algorithms. Our conclusions are given in the last section of the article.
# Microstructured Phononic Crystal Isolates from Ultrasonic Mechanical Vibrations
## 2 Design of 3D Phononic Crystals
As clearly visible from Figure 1b, the opening mode involves masses and beams, while the closing mode is local and only related to beam deformations; thus, resulting in a significant difference in terms of natural frequency and in an ultra-wide bandgap. To verify the claimed attenuation properties in a finite prototype made by \(2\times 2\times 3\) unit cells and fabricated through the 2 PP technique, a non-dimensional transmission diagram was also numerically computed in COMSOL Multiphysics v5.6. The \(2\times 2\times 3\) configuration was chosen as a compromise between attenuation efficiency, which increases with the number of cells and compactness of the overall structure. A glass support and a top plate (\(2a\times 2a\times 14\) um) of the same material of the phononic crystal were also considered in the analysis to simulate the experimental set-up employed in the following. The 3D geometry was discretized through 224,000 quadratic tetrahedral elements. Free boundary conditions were applied on all the lateral surfaces of the phononic crystal and on the surface of the top plate, while a prescribed frequency-dependent \(z\)-axis displacement was assigned at the bottom surface of the glass support, as shown in Figure 1c. A frequency domain analysis was then performed in the range of frequency 0 MHz-8 MHz with a step of 400 Hz. The output was computed for each forcing frequency as the average \(z\)-axis displacement experienced by the upper surface of the top plate, as shown by the black arrow in Figure 1c. The non-dimensional transmission diagram is reported in Figure 1c, it shows a good agreement with the dispersion plot reported in Figure 1b. Three peaks are present in the attenuation dip of the transmission diagram. They correspond to global modes of the top plate, as shown in the inset of Figure 1c and do not compromise the correct functioning of the metastructure, as expected.
## 3 Methodology
### Slope Length (L) and Slope Steepness (S) Factor (LS Factor)  
The LS factor describes the impact of topography on erosion, which is directly proportionate to the slope's length and gradient. The LS factor map was generated using the Digital Elevation Model (DEM) in the ArcGIS environment [6]. The terrain effects on erosion are assessed using the LS parameter, which is the product of slope length (L) and slope steepness (slope angle) (S). The escalating runoff accumulation towards the downslope increases the total soil erosion as the slope length (L) increases. Similarly, as the slope steepness rises, the runoff velocity and erosivity rise consequently [75; 76]. Using ArcInfo, an ArcGIS Spatial analyst extension, the combined LS factor was calculated. The authors of [77; 78] proposed the following equation, which was applied to a 30 m DEM cell size in the present study:  
\[\text{LS}=(\text{Flow Accumulation}\times\text{Cell size}\div 22.13)^{0.4}\ \times(\text{sin \ slope}\div 0.896)^{1.3} \tag{3}\]  
where LS equals the merged slope length and slope gradient factors; flow accumulation represents the cumulative upslope contributing region for a particular cell; cell size equals the size of the grid cell; and sine slope equals the sin of the slope angle in degrees. We used ArcGIS Spatial Analyst Plus together with the Arc hydro extension to estimate the flow accumulation and slope steepness from the DEM. The DEM data were retrieved from EARTHDATA Search [79] by defining the basin through the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) DEM V003. Images of 30 m resolution were then downloaded from ASTER-DEM. We imported these images into  
ArcGIS and mosaicked them using \"Mosaic to New Raster\", a tool in \"Data Management Tools\". After identifying the Universal Transverse Mercator (UTM) zone, the merged map was re-projected. Then, we applied \"Fill Sinks\" from Arc Hydro Tools > Terrain Processing > DEM Manipulation. Next, we selected \"Flow Direction\" and \"Flow Accumulation\" from \"Terrain Processing\" to obtain the flow accumulation. The slope was generated using the ArcGIS 10.4.1 tools Spatial Analyst Tools > Surface > Slope.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Textural Class** & **K Factor (ton/Hectare)** \\ \hline Clay & 0.49 \\ Clay loam & 0.60 \\ Loam & 0.67 \\ Loamy sand & 0.09 \\ Sand & 0.04 \\ Sandy clay & 0.45 \\ Silty clay & 0.58 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Soil features and the corresponding K factor.
## 3 The SensoTube Architecture
### Wireless Networking Layer (WNL)  
The establishment of a discrete functional shield for the wireless data communication, firstly, allows designers to focus on the wireless networking aspects (e.g., routing protocols [115; 116], operating systems [22], new trends [117], new technologies [118; 119; 120], etc.), and, secondly, supports the requirement for the decoupling of applications from the wireless networking field [91].  
According to the SensoTube, a WNL can be implemented in its own PCB with a dedicated MCU on-board. In this way, the WNL shield can collaborate with other functional shields for the sake of any particular application scenario. At this shield, any of the known design practices, i.e., chip-set, SoCs, and modules, can be accommodated, in order to implement the wireless data networking. Contrary to the existing architectures, SensoTube allows for the engagement of numerous WNL shields through its inherent expansion mechanism and its inter-layer services provisions. Thus, challenging implementations, such as for heterogeneous communications, as in the case of [31], can be seamlessly facilitated to the WSAN system. Additionally, the specific inter-layer service provision for energy management, allows the WNL shield to be energy aware of every single operation of its data radio communication sub-systems. The ability to have a complete control and monitoring of energy is of crucial importance for the real-world WSAN applications in the field. Also, a WNL shield, thanks to the holistic strategy for the energy management that is achieved by the inter-layer energy management service, can be entirely powered-ON or OFF from other functional layer shields, in order to minimize the energy consumption. On the other hand, the inter-layer service for signals management eliminates the resources constraints of the existing OSH architectures, while, at the same time, provide the polymorphism in expansion mechanisms, in order to help towards the maximum scalability, openness and reusability. This is very important, in the case of the usage of the various integrated communication modules (e.g., Bluetooth, WiFi, and ZigBee modules) in the design of WSAN nodes. According to the existing expandable OSH architectures, such modules are serially interfaced with the main-board's MCU, in order just to transmit and receive data. In this case, these modules are not fully exploited for the sake of the system. Actually, these modules are built around of a reprogrammable MCU, the signals of which are provided at the module's miniaturized PCB. A WNL shield can fully exploit the capabilities of these modules. In particular, the analog and digital I/O signals of the modules can be routed to the BECs of the system, and also, through the use of the inter-layer service for programming and debugging, to allow for in-system firmware development. Thus, the SensoTube WNL shields can achieve the integration of such modules in a homogeneous and uniform way.
# On Evaluating IoT Data Trust via Machine Learning
## 4 Features
### Correlation Features
#### 4.1.1 Frequency Domain Representation  
Time-series data can be represented in the frequency domain using the coefficients of its discrete cosine transform (DCT). Let \(x_{i}\) be the \(i\)th value of a given time window with \(N\) values. We calculate the DCT coefficients as [19]  
\[a_{k}=\sum_{i=0}^{N-1}x_{i}\cos\left[\frac{\pi}{N}\left(i+\frac{1}{2}\right)k \right]\text{ for }\ k=0,\ldots,M-1 \tag{1}\]  
where \(M\) is the number of DCT coefficients, which is constant for the data of all time windows. We then split the coefficients into ten equal frequency bands and averaged them within each band. The resultant ten average values are our autocorrelation features that can compactly represent the data in the frequency domain. Note that these coefficients do not strictly represent the data autocorrelation, which is defined as the correlation between a time series and its delayed copy as a function of the delay. Rather, they represent the data correlation from a frequency domain perspective.
## 4 Engineering Case Analysis
### Determination of Evaluation Index Weights  
In this survey, two questionnaire survey methods described in this study were employed to collect expert opinions. Subsequently, the Triangular Fuzzy Analytic Hierarchy Process (FAHP) and the traditional Analytic Hierarchy Process (AHP) were used to determine the weights of evaluation indicators. As an example, the weights of evaluation indicators were calculated using the two assessment methods for the Sijiao'an Tunnel, and the results are presented in Table 5.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Serial Number**} & \multirow{2}{*}{**Tunnel Names**} & \multirow{2}{*}{**Start and End**} & \multirow{2}{*}{**Length**} & \multicolumn{3}{c}{**Tunnel Alignment**} & \multirow{2}{*}{**Number of Accidents**} \\  & & & & & & & \\ \cline{5-6}  & & & & & & & \\ \hline \multirow{2}{*}{1} & Sijiao’an Tunnel & K2 + 748–K4 + 140 & 1392 & 0.50 & \begin{tabular}{c} Circular Curve + Transition \\ Curve + Straight Segment \\ \end{tabular} & 84 \\ \hline \multirow{2}{*}{2} & Jiaodong’ao Tunnel & K7 + 660–K9 + 815 & 2155 & \(-\)2.13, 2.5 & \
\begin{tabular}{c} Straight Segment + Circular \\ Curve \\ \end{tabular} & 103 \\ \hline \multirow{2}{*}{3} & Anjishan Tunnel & K37 + 086–K38 + 410 & 1324 & \(-\)1.49, 0.5 &
\begin{tabular}{c} Circular Curve + Transition \\ Curve + Straight Segment \\ \end{tabular} & 10 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Summary of the data for the large tunnels in the surveyed road section.
# Line Scan Spatial Speckle Contrast Imaging and Its Application in Blood Flow Imaging
## Materials and Methods
### Flow Phantom  
The flow phantom consisted of lipofundin MCT/LCT (4%) solutions (B.Braun Melsunen AG, Germany) in a polyethylene tube driven by a digital syringe pump (SPLab01, Baoding Shenchen Precision Pump Co., Ltd., Baoding, China) at a steady flow rate from 0 to 10 mm/s.
## 2 Methodology
### Fixed-Bed Gasifiers
#### 2.1.1 Updraft Gasifiers  
In this configuration, the fuel is loaded in the upper part of the gasifier chamber, and air or oxygen is introduced from beneath, flowing upward through the fuel bed. Gasification reactions occur from top to bottom, passing through moisture removal, pyrolysis, combustion, and reduction stages as illustrated in the following Figure 1a. The fuel that flows through the gasifier from top to bottom contacts the hot gases moving up through the gasifier, and initially the drying process starts. This is followed by the pyrolysis process during which char formation takes place. The char that comes in contact with the combustion products is gasified producing carbon monoxide. These gasifiers are known for their thermal efficiency, easy operational procedures, and ability to accommodate feedstock with elevated moisture and ash contents. However, they produce the largest quantity of tar, have limited scalability, and require a longer start-up time [14]. An experiment was conducted to investigate a modified updraft fixed-bed gasifier and an adapted biomass feeding system aimed at diminishing the percentage of tar in the producer gas [15]. Although the resulting syngas had a caloric power slightly below the standard value for this reactor type, the maximum efficiency achieved in the gasification of woodchips was 77%. A separate experiment involving a modified updraft fixed-bed gasifier coupled with an adjusted biomass feeding mechanism was designed to decrease the tar levels in the producer gas [16]. This study revealed that the gasification efficiency was contingent on various factors, including the equivalence ratio, biomass characteristics, gasification agent, and gasifier setup.
# On Nash Equilibria in Non-Cooperative All-Optical Networks +
## 1 Introduction
### Related Work  
Several routing games have been shown to possess pure Nash equilibria or to converge to a pure Nash equilibrium independently from their starting state (see [4; 5; 6; 7; 8; 9; 10; 11; 12; 13; 14] for some pioneering work and [15] for an introduction to algorithmic game theory). The price of anarchy has been introduced in [12] for the first time in the literature; it measures the loss of the global performance of the system at equilibrium due to the lack of cooperation among the agents, and is defined as the worst-case ratio between the total cost of a Nash equilibrium and that of an optimal solution. One of the most studied and interesting research areas lying on the boundary between computer science and game theory consists of bounding the price of anarchy of selfish routing under different models; see, for example [13; 14].  
Game theory has been applied to optical networks in various contexts (e.g., see [16; 17; 18]). For instance, it is worth noting that the optimization of the network cost due to expensive hardware components (e.g., add-drop multiplexer) has been widely investigated in the literature (see [19; 20; 21; 22]), also considering the effect of collusion among agents (see [23]). Moreover, in [16], the authors deal with a setting very similar to the one addressed in this paper; they consider several natural cost functions, and for each of them, they examine the problem of the existence of pure Nash equilibria, and of the complexity of recognizing and computing such equilibria.
# Effects of Intrinsic Factors on the Stability of Silver Nanowire-Based Flexible Electrodes
## 3 Results and Discussion
### Effects of Flexible Substrates on the Stability of AgNW Electrodes
locations, which will cause the silver nanowires to granulate and the conductive pathway be destroyed. For the PVA-AgNW electrodes, due to the wrapping effect of the PVA film on the silver nanowires, the damage caused by light illumination to the silver nanowire network connection can be effectively prevented, resulting in fewer broken wires on the electrode surfaces. Therefore, the use of the PVA substrates has a great contribution to the reduction in the surface activity of AgNW electrodes due to the wrapping effect and can improve the stability of AgNW electrodes greatly. Therefore, to further improve the stability of the AgNW-based electrodes, a protective layer should cover the exposed AgNW surfaces in the application process. \begin{table}
\begin{tabular}{c c c} \hline \hline \multirow{2}{*}{**Exteral Conditions**} & **Square Resistance Change After 7 \(\times\) 24 h of Placement (\%)** \\ \cline{2-3}  & **Thermal Stability at 80 \({}^{\circ}\)C** & **Light Stability Under** \\ \multicolumn{1}{c}{**Intrinsic Parameters**} & **Treatment** & **26.0 W/m\({}^{2}\) of Illumination** \\ \hline PET–AgNWs@64 mg/m\({}^{2}\) & 167.2 & 380.0 \\ \hline PET–AgNWs@95 mg/m\({}^{2}\) & 105 & 100.2 \\ \hline PET–AgNWs@126 mg/m\({}^{2}\) & 98 & 49.3 \\ \hline PET–AgNWs@126 mg/m\({}^{2}\) with GO modification & 69.4 & 32.7 \\ \hline PVA–AgNWs@64 mg/m\({}^{2}\) & 67.1 & 121.3 \\ \hline PVA–AgNWs@95 mg/m\({}^{2}\) & 48.2 & 32.3 \\ \hline PVA–AgNWs@126 mg/m\({}^{2}\) & 45.1 & 16.2 \\ \hline PVA–AgNWs@126 mg/m\({}^{2}\) with GO modification & 31.7 & 10.8 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Comparisons of the stability of AgNW electrodes with different intrinsic parameters. Figure 5: AFM images of the surfaces of AgNW electrodes with 95 mg/m\({}^{2}\) of AgNW surface density at an ambient temperature of 25 \({}^{\circ}\)C. (**a**) PET–AgNWs, and (**b**) PVA–AgNWs.
# AI-Driven Waste Management in Innovating Space Exploration
## 3 Traditional Waste Management Practices in Space
### Ground-Based Simulations and Testing  
Before deploying a waste management system in space, it undergoes rigorous ground testing to simulate microgravity using parabolic flights, drop towers, or neutral buoyancy labs. These tests ensure that the system operates effectively without Earth's gravity and identify necessary modifications. Prototypes are then evaluated aboard the International Space Station (ISS) to assess their performance in a microgravity environment. They involve real-time testing and iteration to integrate with existing life support systems and evaluate operational efficacy over time. Advanced computer simulations also play a vital role in predicting system functions under various space conditions, helping to identify potential failures early in development. This approach saves time and resources by refining designs before physical deployment. Once operational, sensors and monitoring devices collect data on energy consumption, waste processing efficiency, and containment integrity, providing essential evidence for ongoing optimisation [55; 56]. Feedback from all testing phases drives continuous improvements, enhancing reliability, efficiency, and safety. The development process engages a diverse community of researchers and engineers to incorporate the latest scientific and technological advances. Extended mission simulations on Earth, in habitats mimicking space station conditions, test the systems' durability for deep-space missions and future lunar or Martian bases. This comprehensive validation ensures that waste management systems are theoretically sound and practically viable in harsh space conditions, contributing to mission sustainability and crew safety [57; 58; 59]. Figure 2 illustrates the daily waste by each astronaut, highlighting the cumulative impact over time.  
Figure 2: Average daily waste generation per crew member on the ISS.
# A Review of Wireless Positioning Techniques and Technologies: From Smart Sensors to 6G
## 3 Wireless Technologies
### ZigBee  
The ZigBee technology specifies the PHY and MAC layers and is based on the IEEE 802.15.4 standard, which adds the network (NWK) and application layer (APL) specifications on top of it to complete the full ZigBee stack [100], as shown in Figure 15.  
ZigBee operates in the unlicensed ISM band at 2.4 GHz, offers data rates up to 250 kbits [93], and supports simple devices with minimal power operating in the personal operating space (POS) of 10m. It also provides self-organized, multi-hop and reliable mesh networking with long battery lifetime. ZigBee networks consist of three types of nodes, the gateway, static, and mobile nodes. The gateway is used for interconnecting the network to another node or network, the static nodes are deployed in known locations and act as reference nodes, and the mobile nodes are the ones that need to be localized. The mobile nodes are usually worn or carried by people, have lower computational capabilities, and are incapable of performing any network-related services.  
For instance, the ZigBee indoor monitoring system in [100] is based on RSSI measurements and aims at helping the school authorities keep track of children in school premises and even locate teachers in case of an emergency. The localization algorithm consists of the collection of the raw RSSI measurements, followed by the deterministic phase (calibration) and probabilistic phase (smoothing). Finally, the position is estimated by iterative trilateration. The mobile nodes were embedded in the students' and teachers' ID cards. The gateway was configured to periodically broadcast messages to the static nodes for updating the network information. Compared to LoRa, the ZigBee network  
Figure 15: ZigBee stack reproduced with permission from [PERSON], _Research and Application of ZigBee Protocol Stack_, published by IEEE, 2010.  
is established using a single static channel for communication, so is more susceptible to interference. Another ZigBee weakness is its inability to communicate with smart devices directly, without additional hardware.
# Review on Active and Passive Remote Sensing Techniques for Road Extraction
## 2 Overview of the Existing Data Acquisition Techniques for Road Extraction
### Airborne Laser Scanning (ALS)
#### 2.4.2 Typical Sensors  
The biggest ALS manufacturers include Leica Geosystems (Switzerland), Teledyne Optech (Canada) and RIEGL (Austria). Examples of the current system are listed in Table 3. It can be seen from Table 3 that ALS can collect one to several million points per second, which secure the usability of the collected data for most surveyed and mapping cases. Meanwhile, the lidar systems can be used both the low-altitude platforms (UAV and helicopter) and high-altitude ones (fixed-wing aircraft). In addition, most ALSs do not operate in eye-safety wavelength: typical operating wavelengths for ALS systems are 532 (green), 1064 (near-infrared) and 1550 nm (shortwave infrared). The point density and accuracy depend on the flying height, reaching a maximum of 60 points/m\({}^{2}\). In addition, its accuracy depends on the range measurement accuracy combining with attitude measurement accuracy. In addition, small sensors are available for UAVs.