esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Discussion of Academic Literature and Council Uses
### Waste and Recycling  
In the field of waste management and recycling, some councils are turning to drones to detect illegal waste, marking a significant advancement in this area. Beyond the usage, drones equipped with sensors can identify odours from wastewater treatment plants, reducing the need for human analysis and improving the early detection of issues in septic systems. Drone mapping is also employed for high-resolution aerial surveys, which are particularly useful in tasks like beach litter assessments. Moreover, drones can pinpoint locations of illegal waste incineration, using algorithms designed for pollution source detection.
###### Abstract
The NARA is a Beechcraft King Air 350 HW that can carries a total of five researchers, including the pilot, and can fly for approximately 7 hours to an altitude of 10 km. It is equipped with atmospheric/cloud observation devices such as a CCN-200 (cloud condensation nuclei counter), CCP (cloud combination probe), PIP (precipitation imaging probe), and Sky-OPC (optical particle counter). This aircraft performs atmospheric observation for weather modification and analysis of climate change and weather phenomena [7; 21]. Precipitation enhancement experiments for weather modification have gradually increased in number due to the growing need for research on dam watershed water resources, forest fire prevention, fog dissipation, and fine dust reduction [3; 7; 22]. To verify and analyze precipitation enhancement experiments, studies have been performed using numerical simulations [23; 24] and ground/space observational data (radar, lidar, and satellite) [25; 26; 27]. Satellite data is very useful because it enables the continuous monitoring of large areas. [PERSON] et al. [28] and [PERSON] et al. [29] used satellite data to analyze cloud occurrence and characteristics. It is important to thoroughly review locations for conducting precipitation enhancement experiments and to determine whether clouds suitable for seeding occur. Therefore, our study analyzed the occurrence frequency and distribution of seedable clouds to be able to conduct better precipitation enhancement in weather modification experiments using atmospheric aircraft in South Korea. The occurrence frequency of seedable clouds is a research topic recommended by the World Meteorological Organization (WMO) climate change guidelines [30]. Consequently, a principal task for weather and climate change researchers is to investigate the distribution and characteristics of clouds. This research can be utilized by future studies, such as relieving drought and preventing forest fires, in addition to helping secure future water resources.
## 5 Major Findings and Outlook  
### Major Findings  
From our findings above, we can see that Internet finance modes include Internet banking, crowdfunding, P2P lending, big data finance, digital currency and fintech. And we divide them into three stages according to their development level. The first stage is Internet banking. The second stage includes modes like P2P lending and crowdfunding and the third stage includes modes like fintech, big data finance and digital currency. In addition, we found that during literature analysis, simultaneous co-word analysis and co-citation analysis can avoid missing important results to a certain extent.  
* Internet banking. Research related to Internet banking is the earliest. In the early days, it mainly studied the influence of various factors such as risk perception, perceived benefits, attitudes and perceived usefulness on user adoption of Internet bank. Later studies focused on the impact of factors such as trust, security, authentication and customer service quality on user loyalty and user usage depth of Internet bank and the research goal turned to the use of mobile banking. The research angle expands from the perspective of the earliest interests and trust to national culture, from the perspective of developed countries to developing countries.
* P2P lending and crowdfunding. The researches of P2P lending and crowdfunding are still developing, which still have potential to explore. And research hotspot focused on these modes. In terms of P2P lending, the content of its research is related to P2P lending success factors like ethnic differences, information asymmetry, herd effect and default prediction. And the main research content is information asymmetry, which is also a research hotspot. As for crowdfunding, one main research content refers to determinants of project crowdfunding success such as information on crowdfunding project sponsors, the quality of crowdfunding projects, the types of crowdfunding projects and investor satisfaction and donors' behavior. Other research contents include the design of crowdfunding mechanism, the influence of social network on crowdfunding and the use of equity crowdfunding or product crowdfunding. We can study crowdfunding from the perspective of investors, regulators and sponsors.
* Big data finance, fintech and digital currency. The third stage involves fintech, big data finance and digital currency. Their research content is small but constantly enriched and developed. The rapid development of bitcoin has brought the research upsurge of digital currency. Its essence is the main research direction of price decision-making mechanism. The current research on fintech mainly is using big data to predict changes in asset market.
# Design and Implementation of an Indoor Localization System Based on RSSI in IEEE 802.11 ax
###### Abstract  
This article describes the design, implementation, and evaluation of an indoor localization system based on Received Signal Strength Indicator (RSSI) measurements in wireless sensor networks. While the majority of the literature uses the IEEE 802.15 standard for this type of system, all of the measurements in this study were performed using a test bench operating under the IEEE 802.11 ax standard in the 2.4 GHz band. RSSI is widely used due to its simplicity and availability; however, its accuracy is limited by signal attenuation, electromagnetic interference, and environmental variability. To mitigate these limitations, the present work proposes the implementation of advanced techniques, including weighted averages and positioning algorithms such as Min-Max, Maximum Likelihood, and trilateration, aiming to achieve an accuracy of 2 m in controlled conditions. The design also included a specialized test bench to calculate the coordinates and estimate the location of unknown nodes using anchor node positioning. This approach combines the simplicity of RSSI with optimized algorithms, providing a robust and practical solution for indoor localization. The results validate the system's effectiveness and highlight its potential for future applications in real-world environments, opening new possibilities for optimizing wireless sensor networks and addressing the current challenges in localization systems.  
indoor localization; RSSI; IEEE 802.15; IEEE 802.11 ax; wireless sensor networks; IoT 2025
# Joint QoS and Congestion Control Based on Traffic Prediction in SDN
## 3 System Architecture
An outline of the resource allocation in our scheme is presented in Algorithm 1. Consider the network is in a steady state and a new flow is arrived (line 2 of the algorithm). The controller allocates the resources to the mentioned flow based on typical routing protocols such as ECMP [29] (line 3 of the algorithm). The controller calculates the utilization rate of the links periodically. If the utilization rate of the network links passes a predefined threshold, the controller reallocates the network resources using the proposed scheme (lines 4 and 5 of the algorithm). To this end, QRTP uses the current network traffic and the estimated one, to reschedule the traffic flows in a way that minimizes the packet loss. Figure 2 illustrates a visual process of the proposed scheme. As can be seen, in this architecture, a typical routing algorithm routes one flow in each step while the proposed rerouting algorithm reroutes several flows to reduce the packet loss and provides a better QoS to the users. ```
1:while true do
2:if new flow arrives then
3: Traditional Routing Algorithm
4:else if congestion is detected or predicted then
5: Proposed Rerouting Algorithm
6: Reset timer
7:else if timer elapses then
8: Proposed Rerouting Algorithm
9: Reset timer
10:endif
11:endwhile
```  
**Algorithm 1** : Outline  
Figure 1: The architecture of the proposed scheme. The architecture is composed of three main layers (i) Application Layer (the upper layer); (ii) Control Layer (the middle layer); and (iii) Infrastructure Layer (the down layer). Our main contributions are in the Application Layer.
# Self-Isolated Dual-Mode High-Pass Birdcage RF Coil for Proton and Sodium MR Imaging at 7 T MRI
## 2 Materials and Methods  
### FDTD EM Simulation  
Electromagnetic (EM) simulation based on finite difference time domain (FDTD) [36] was utilized to predict the RF coil's performance at both the \({}^{1}\)H and \({}^{23}\)Na frequency using Sim4 Life (ZMT, Zurich MedTech AG, Zurich, Switzerland) [37]. A 12-leg high-pass tapered birdcage RF coil, as shown in Figure 1, was designed for both \({}^{1}\)H and \({}^{23}\)Na transmission and reception based on the following specifications: upper diameter = 153 mm; bottom diameter = 250 mm; length of legs = 210 mm; width of legs and end-rings = 20 mm; resonant frequency of \({}^{1}\)H = 298 MHz; resonant frequency of \({}^{23}\)Na = 78.9 MHz at 7 T. The optimized capacitor values were calculated through the RF circuit co-simulation method [38], which provides more reliable capacitor values compared to the previous birdcage calculator based on inductance measurement [39]. For the \({}^{1}\)H coil simulation, the end-ring capacitors were 3.7 pF and 2.6 pF for the upper and bottom end-ring, respectively. For the \({}^{23}\)Na coil simulation, capacitors of 85.5 pF and 45.35 pF were used at the upper and bottom end-ring. These simulations were performed on a three-dimensional (3D) human model, \"Duke\" [40], to assess B\({}_{1}^{+}\)-field uniformity and specific absorption rate (SAR). The B\({}_{1}^{+}\)-field uniformity was calculated in the human model at the center of the RF coil.  
\begin{table}
\begin{tabular}{c c c} \hline
**Design Type** & **Advantages** & **Challenges** \\ \hline Active switching with pin-diode [26; 27; 33] & Widely utilized due to available pin-diode & Sensitivity reduction when the pin-diode is \\  [26; 27; 33] & drivers in MR systems & forward-biased \\ \hline FS trap circuit & Achieves dual-tuning at two frequencies & Performance degradation at proton frequency \\  [28; 29] & using a single birdcage RF coil & Complex adjustment of trap and \\  & & capacitor values \\ \hline Frequency blocking & Allows dual-tuning by integrating traps & Requiring a doubling of leg count for B\({}_{1}\) \\  [30] & into each leg of a single birdcage RF coil & field homogeneity \\ \hline Four end-ring & Superior SNR compared to alternating leg & Increasing overall coil length and restricting \\  [31; 32] & designs. No additional lossy components & patient space, especially in brain imaging \\ \hline \end{tabular}
\end{table}
Table 1: Advantages and challenges of several dual-tuned RF coil design.
## 4 Charging Method
### Constant Current (CC) Charging Method  
The constant current (CC) charging method, as depicted in Figure 12, is a widely used and uncomplicated conventional charging technique. It ensures that the battery is charged at a consistent low C-rate throughout the entire charging cycle. Once a certain threshold is reached, the credit card will cease to be charged. The following method is widely used for charging NiCd, NiMH, and Li-ion batteries.  
The charging current rate plays a crucial role in determining the overall performance of the battery in this process. The optimal charging current for a CC is a challenging aspect to determine as it needs to strike a balance between minimizing charging time and optimizing energy utilization. While a higher charging current facilitates a rapid recharge of the battery, it concurrently expedites the process of battery degradation. The high-capacity utilization achieved by the low charging current is counterbalanced by the inconvenience it poses for EV applications due to the extended charging durations [69].  
\begin{table}
\begin{tabular}{c c c} \hline \multicolumn{3}{c}{**Three-Phase Charger**} \\ \hline \multicolumn{3}{c}{**Pros**} & \multicolumn{2}{c}{**Cons**} \\ \hline \(\bullet\) & Faster than single-phase chargers at recharging EVs. & \(\bullet\) & Cost: Chargers that operate in three phases are more expensive than those that operate in one phase. \\ \(\bullet\) & Since the current is distributed throughout the circuit. & \(\bullet\) & Installation: Three-phase chargers require extra wire, which makes them more challenging to install. \\ \(\bullet\) & More effective than chargers that operate in one phase. & \(\bullet\) & \(\bullet\) \\ \hline \end{tabular}
\end{table}
Table 13: Critical analysis of benefits and drawbacks of three-phase charger.  
\begin{table}
\begin{tabular}{c c c} \hline \multicolumn{3}{c}{**Single-Phase Charger**} \\ \hline \multicolumn{3}{c}{**Pros:**} & \multicolumn{2}{c}{**Cons:**} \\ \hline \(\bullet\) & Less wire is needed compared to three-phase chargers, & \(\bullet\) & Time: Three-phase chargers charge faster than single-phase chargers. Hence, it is not appropriate for quicker charging speeds. \\ \(\bullet\) & As most residences only have single-phase power, it is & \(\bullet\) & Safety: If improperly placed, single-phase chargers might be hazardous to operate. \\ \(\bullet\) & Ideal for low-power charging requirements. & \(\bullet\) & \(\bullet\) \\ \hline \end{tabular}
\end{table}
Table 12: Critical analysis of benefits and drawbacks of Single-Phase Charger.
## 3 Results and Discussion  
### TL Glow Curve  
In the absence of any effect of external laboratory irradiation doses and at relatively elevated temperature, the TL signals of the as-received phyllite demonstrate doses accumulation behavior. For a second readout, the signals background for the sample and reader were measured. The TL glow curve of the as-received phyllite sample is almost constant with little intensity variation. When the phyllite sample was heated (with a linear rate of order 5 \({}^{\circ}\)C/s) from room temperature up to 400 \({}^{\circ}\)C, the glow curves approach only a single peak, observed at 250 \({}^{\circ}\)C (Figure 1). This behavior can be explained based on the trap centers that exist in the as-received sample. The natural sample (phyllite) contains trap centers that are empty at low and room temperatures. These centers are empty because fading behavior was observed during the transition from low temperature to room temperature. In addition, the TL signals measured from the as-received specimen are mainly ascribed to two parts--the first is due to self-irradiation, and the second is a result of irradiation acquired from the surrounding environment.
## 4 Effect of Fault Size Extension on Bearing Dynamic Characteristics
### Bearing Outer Ring Stress Change and Crack Extension Trend
#### 4.2.1 Maximum Shear Stress
To provide a clearer view of the variation trends in maximum shear stress peak values under different fault types for the two materials, a comparison of the maximum shear stress peak values during the entry and exit of faults for both materials is presented in Figure 12.  
Figure 11: Max shear stress curve of different types of faults. (**a**) Material GCr15 enters the failure stress curve. (**b**) Material GCr15 exits the fault stress curve. (**c**) Material AISI304 enters the failure stress curve. (**d**) Material AISI304 exits the fault stress curve. From Figure 12, it can be observed that when the rolling elements experience only microscopic sliding on the inner raceway of the outer ring, the maximum shear stress during fault entry and exit gradually increases, with the maximum shear stress during fault exit being higher than during fault entry. This indicates that as fault severity increases, the crack propagation speed also increases. From Figure 12a,b, it can be seen that when macro-slipping occurs in the rolling elements along the outer ring raceway, the maximum shear stress during the entry and exit of faults shows a decreasing trend for fault types 3-4 in GCr15 and 4-5 in AISI304. However, for GCr15, when the fault size reaches 1.25 mm, there is an increase in maximum shear stress during both entry and exit from the fault, indicating fluctuations in maximum shear stress during macro-slipping. Initially, the occurrence of macro-slipping results in a decrease in maximum shear stress. However, this does not imply a slowdown in crack propagation speed, as the friction generated by macro-slipping, combined with the maximum shear stress, also promotes crack growth.
# A Complete Pipeline for Heart Rate Extraction from Infant ECGs
## 2 Materials and Results
### The HR Pipeline
#### 2.3.3 Correction for Shifted Beats  
Wrongly located R-peaks can remain undetected by the median filter approach described above. A useful observation is that an early labelled beat leads to a much greater heart rate rise followed by a much steeper heart rate drop than typically appears in a natural signal (Figure 11c). A late-labelled beat does the opposite. The proposed algorithm searches for the presence of three consecutive sign changes concurrently with a large variation in the heart rate difference (>15 bpm for the first and third heart rate gaps, >25 bpm for the middle gap), thus identifying the mislabelled beats within a signal, provided the neighbouring beats are correct. Areas with large amounts of mislabelled beats are likely to be caught by the algorithm for missing/additional beats and are likely one reason for the more conservative thresholds present In the processed HR tests.
###### Abstract  
The structural integrity of post-tensioning prestressed concrete structures with tendon ducts highly depends on the grouting quality in construction. This paper proposes a real-time approach to monitoring the grouting compactness in tendon ducts using the multi-sensing electro-mechanical impedance (EMI) method. When Lead Zirconate Titanate (PZT) transducers with different pre-selected dimensions are serially connected and mounted on a structure at distributed locations, each PZT provides unique resonance frequency coupled with the local structural physical property. Therefore, the impedance with multiple peaks of the serially connected multiple PZTs can be captured during a single measurement, which significantly simplifies the measurement procedure and reduces the data processing time. In addition, the wiring for the PZT sensors is also simplified. In this research, the feasibility of the proposed method was experimentally and numerically investigated to monitor the grouting compactness in a tendon duct specimen. The 3-dB mean absolute percentage deviation (MAPD) was applied to quantify the variations of the impedance signatures measured from five different grouting levels. Both experimental and numerical results verify the feasibility of using the proposed method for monitoring the grouting compactness in tendon ducts.  
Keywords:post-tensioning prestressed concrete; grouting compactness; multi-sensing electro-mechanical impedance (EMI) method; lead zirconate titanate (PZT) transducer; 3-dB mean absolute percentage deviation (MAPD) +
Footnote †: journal: Applied Sciences
# A Software-Defined Networking Framework to Provide Dynamic QoS Management in IEEE 802.11 Networks
## 2 Contention Window Adaptation Mechanism
### The Proposed Mechanism
#### 2.2.2 Gain Calculation in Asymmetric Scenarios  
The gain value deduced in Section 2.2.1 supposes that all the stations use the same initial \(CW_{min}\) value. However, as a consequence of our QoS-aware medium access control algorithm, it would be possible to find an scenario where nodes have different initial values of \(CW_{min}\). In Appendix B, it is developed a mathematical study to show that the gain \(G\) is practically independent of the initial window size (\(CW_{min}\)) of the participants (see Equations (A8) and (A9)).
# Vectored-Bloom Filter for IP Address Lookup: Algorithm and Hardware Architectures
## 4 Hardware Architecture
### Parallel Architecture  
The IP address lookup performance using the VBF can be effectively improved by applying parallelism. Figure 4 describes the parallel architecture using two basic IP address lookup modules. Two new blocks are implemented for this parallel architecture: a _Distributer_ and an _Output Queue_. The _Distributer_ provides inputs to each module when the module is ready for a new input, while the _Output Queue_ provides the output ports according to the order of arrived inputs.  
Figure 4: Parallel architecture consisting of two basic IP address lookup modules: the bold lines represent data paths and the dotted lines represent control paths.
## 4 Anomaly Detection
### Hidden-State Estimation of Auto-Regressive Model  
For offline construction of the state and log-likelihood pairs, we are interested in the most likely state sequence upon an observation sequence \(y_{0:T}\). One might be derived from copulating  
the MAP sequence by maximizing the marginal probability at each observation \(i\)  
\[\hat{z}_{i}=\underset{z_{i}}{arg\ max}\ p(z_{i}|y_{0:T}). \tag{21}\]  
We note this combined single-observation estimated sequence might yield unlikely (even 0-probability) sequences. We therefore consider  
\[\hat{z}_{1:T}=\underset{z_{i:T}}{arg\ max}\ p(z_{1:T},y_{0:T}). \tag{22}\]  
where \(p(z_{1:T},y_{0:T})\) was computed in Equation (17). Actually, we note the most likely state sequence that the minimum cost path to \(z_{t}\) is equivalent to the minimum cost path to node \(z_{t-1}\) plus the cost of a transition from \(z_{t-1}\) to \(z_{t}\), and the cost incurred by observation \(y_{t}\).  
For convenience, we abbreviate the joint log-likelihood function \(\mathcal{L}(z_{1:T})\triangleq log\ p(z_{1:T},y_{0:T})\), and the transition probability \(\pi_{z_{t-1}}\triangleq z_{t-1}\), then  
\[\mathcal{L}_{T}(z_{1:T})=s_{1}(z_{1})+\sum_{i=2}^{T}s_{t}(z_{t},\pi_{z_{t-1}}), \tag{23}\]  
where  
\[\begin{split} s_{1}(z_{1})&=log\ (\pi_{z_{1}}p(y_{1}|\theta_{z_{1}},y_{0})),\quad t=1\\ s_{t}(z_{t},z_{t-1})&=log\ (p(z_{t}|z_{t-1})p(y_{t}| \theta_{z_{t}},y_{t-1})),\ t\geq 2\end{split} \tag{24}\]Obviously, \(\mathcal{L}_{t}(z_{1:t})=\mathcal{L}_{t-1}(z_{1:t-1})+s_{t}(z_{t},z_{t-1})\), and set  
\[\begin{split} v_{t}(z_{t})&=\underset{z_{1:t-1}}{ \max}\ \mathcal{L}_{t}(z_{1:t}),\qquad z_{t}\in\{1,2,3,\ldots,K\}\\ v_{t}(z_{t-1})&=\underset{z_{t}}{\max}\ \{v_{t-1}(z_{t})+s_{t }(z_{t},z_{t-1})\},\end{split} \tag{25}\]  
From the above, the maximizing state sequence is iteratively obtained, for \(n\in\{T-1,T-2,\ldots,1\}\)  
\[\hat{z}_{T}=\underset{z_{t-1}}{arg\ max}\ v_{n}(z_{t-1}), \tag{26}\]  
Assume that we recorded \(N\) sequential data for each skill and the length of sequence \(n\in N\) is \(T_{n}\). Thus, we can get a set of the most probable states vector of each skill  
\[\mathcal{Z}^{1:N}=\{\mathcal{Z}^{1}_{T_{1}},\mathcal{Z}^{2}_{T_{2}},\ldots, \mathcal{Z}^{N}_{T_{N}}\}. \tag{27}\]