esa-sceva/satcom-chunk-collection huggingface dataset:
# AVSS: Airborne Video Surveillance System
## 5 AVSS Features
### Event Detection and Video Quality Selection Algorithm  
Due to the limited storage of the UAV, storing the video in maximum quality throughout the mission is inefficient. Further, a typical surveillance system, overwrites the oldest data without consideration of its contents when the storage is full. However, most of captured images are unnecessary with no event, so intelligent data storing can greatly improve the storage usage. Our algorithm detects events in the scene and stores the data based on the event metric.  
Considering the limited computational power, the event detection algorithm uses optical flow, which is computationally cheap. Algorithm 1 depicts the procedure of the event detection and the video quality selection. \(F(t)\) indicates the frame image at \(t\), \(OF(t)\) indicates the optical flow values of \(F(t)\), \(\overline{OF(t)}\) indicates mean for optical flow vector from each pixel, \(\delta\) indicates a threshold value for a pixel to have an event, \(\gamma\) indicates the minimum number of pixels for a frame to be an event, and \(VQI\) indicates the visual quality index value for the compression rate of the frame. As a preprocessing step, the algorithm normalizes each vector by subtracting the mean value from all vectors, to compensate the UAV movement because the horizontal movement, tilt, or span is going to cause all pixels to have the same directional vector. Vertical movements are rare unless the UAV is assigned to a new target area with different size. Afterwards, the module checks the optical flow value to see if any event is present. If a predefined number of optical flow values are greater than a set threshold, the module considers the frame to have captured an event. According to the result of the event detection, algorithm calculates the visual quality index of the frame. When consequent frames have no detected events, the video quality index value is slowly decreased. When an event is detected, the video quality index value is increased in a much greater degree to quickly respond to the event.  
```
1:\(OF(t)\leftarrow\) Calculate optical flow between \(F(t)\) and \(F(t-1)\).
2:\(OF(t)\gets OF(t)-\overline{OF(t)}\)
3:for all\((x,y)\in OF(t)\)do
4:if\(OF(t).x>\delta\) or \(OF(t).y>\delta\)then
5:\(event\_count\gets event\_count+1\)
6:endif
7:endfor
8:if\(event\_count>\gamma\)then
9: Event detected.
10:\(VQI\gets VQI+20\)
11:else
12: Event not detected.
13:\(VQI\gets VQI-1\)
14:endif
15:if\(VQI>100\)then
16:\(VQI\gets 100\)
17:elseif\(VQI<10\)then
18:\(VQI\gets 10\)
19:endif
```  
**Algorithm 1** Event detection and video quality decision.
# Adaptive Multi-Grained Buffer Management for Database Systems
## 4 Performance Evaluation
### Workloads  
The target trace file has a sequence of read-write operations on tuples. We divide the storage device pages into two types, namely, hot pages and cold pages. The size of hot pages accounts for 20%, which will absorb 80% of query operations, meaning most queries will concentrate on the hot pages. We define two types of queries, namely, narrow-queries  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Symbol** & **Description** \\ \hline \(D\) & The database size (e.g., 10 GB) \\ \hline \(P\) & The page size (e.g, 4 KB) \\ \hline \(T\) & The tuple size (e.g., 128 B) \\ \hline \(M\) & The whole buffer size (e.g., 128 MB) \\ \hline \hline \end{tabular}
\end{table}
Table 1: Parameters of the buffer manager.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Method** & **Hot Tuples in the Buffer** & **Hit Ratio** \\ \hline LRU & \(\frac{0.2\cdot M}{T}\) & \(\frac{M}{T}(M<T)\) \\ \hline AMG-Buffer & \(\frac{(0.12+0.32)\cdot M}{T}\) & \(\frac{1.9\cdot M}{D}(M<\frac{5\cdot D}{11})\) \\ \hline \hline \end{tabular}
\end{table}
Table 2: Theoretical comparison between LRU and AMG-Buffer.  
(\(N\)Qs) and wide-queries (\(W\)Qs). Every \(N\)Q reads or writes one tuple of the page; every \(W\)Q reads or writes several tuples of the page. For simplification, we define the ratio of \(N\)Qs among all queries (\(N\)Qs+\(W\)Qs) as _hybrid ratio_. We build various workloads by configuring different hybrid ratios and different read-write ratios, as shown in Table 3. In the trace names, the character \(R\) represents the read ratio and the symbol \(H\) represents the hybrid ratio. For example, in the \"R20-H50\" workload, \"R20\" means that the read ratio is 20% among all requests and \"H50\" means that the hybrid ratio is 50% (NQs account for 50%).  
To demonstrate the effectiveness of AMG-Buffer, we conduct experiments under various workloads and settings, including different memory sizes, hybrid ratios, and read/write ratios. In addition, we also evaluate the adaptivity of AMG-Buffer using dynamically changing workloads. Finally, we test the performance of AMG-Buffer using a large data set to see whether AMG-Buffer can adapt to large data sets.
# A Hybrid CNN-GRU-LSTM Algorithm with SHAP-Based Interpretability for EEG-Based ADHD Diagnosis
## 4 Results
### Exploratory Analysis and EEG Feature Visualization
The international 10-20 system was used to categorize the recording channels, with each horizontal row of the graph representing a different channel. Studies have shown that children with ADHD display characteristic EEG patterns, negligence in sustained attention, impulsivity in increased concentration, and hyperactivity. Changes in amplitude-frequency characteristics and disruptions to rhythm synchronization across brain regions may reflect these features. The analysis of the EEG recording from a child with ADHD reveals characteristic features, including irregular amplitude characteristics, sudden spikes, and periods of reduced activity, which may indicate instability in neural activity regulation. The rapid shifts between frequency ranges, with a predominance of slow rhythms (theta range) and abrupt transitions to high-frequency rhythms, reflect signal variability associated with difficulties sustaining attention and impulse control. The identified patterns distinguishing EEG recordings of children with ADHD from those of TD participants can be utilized in the development of machine learning algorithms for automated EEG signal classification and improved diagnostic accuracy of this disorder. Figure 15 presents the results of ICA performed on EEG data from a child with ADHD, where the topographic maps illustrate the spatial distribution of independent components, reflecting the localization of various activity sources on the scalp. Unlike healthy participants, whose maps exhibit an orderly structure corresponding to stable neural network function, children with ADHD show more complex or shifted patterns, which may indicate disruptions in functional connections regulating attention and impulse control. The obtained results confirm the presence of specific neurophysiological markers that differentiate children with ADHD from the TD population, making the ICA method a valuable tool for further investigation of the mechanisms underlying this disorder and the development of automated diagnostic methods. Such components may reflect increased spontaneous excitability or difficulties in suppressing artifacts related to hyperactive behavior. ICA helps identify these features by distinguishing between the noise signal and physiologically relevant processes. Consequently, the examination of EEG components on topographic maps in children with ADHD provides a more comprehensive understanding of potential impairments in cognitive regulation and facilitates further investigation into specific activity patterns that could be used as biomarkers for this condition. Figure 14: Raw EEG signals for ADHD class.
# Crushing Analysis and Optimization of Adjacent Variable Thickness Hexagonal Tubes
###### Abstract  
In this study, we proposed a new adjacent variable thickness hexagonal tube (AVTHT) and performed crushing analysis and crashworthiness optimization under multiple loadings. First, the finite element models were constructed and validated by experiments with four configurations of AVTHTs. Then, the numerical simulations under axial loading and multiple oblique loadings indicated that AVTHTs under various loading angles (0\({}^{\circ}\), 10\({}^{\circ}\), 20\({}^{\circ}\), and 30\({}^{\circ}\)) and three patterns (\(\alpha\), \(\beta\), and \(\theta\)) exhibited different deformation modes, force-displacement characteristics, and crashworthiness indices. This suggested that we could change and determine the plate thickness configuration to make the AVTHTs exhibit the expected crushing performance under multiple loadings. Therefore, multi-objective optimization for minimizing maximum crushing force with multiple loadings (F\({}_{\text{maxw}}\)) and maximizing specific energy absorption with multiple loadings (SEA\({}_{\text{w}}\)) by changing the thickness configuration under multiple loadings was conducted. The results determined the thickness design domains and indicated that certain thickness ranges should be avoided, such as the ranges of \(1.55\leq t1\leq 1.6\) and \(1.85\leq t1\leq 1.95\), which was helpful for getting AVTHTs to achieve excellent crushing performance in railway vehicles. In the pareto results, increasing \(t1\) would not always increase the F\({}_{\text{maxw}}\) and SEA\({}_{\text{w}}\). For example, when \(1.75\leq t1\leq 1.8\), increasing \(t1\) would lead to decline of F\({}_{\text{maxw}}\) and SEA\({}_{\text{w}}\).  
adjacent variable thickness hexagonal tube (AVTHT); plate thickness configuration; axial and oblique loading; multi-objective optimization (MOD) +
Footnote †: journal: Applied sciences
## 2 Experimental Program
### Analysis of Contaminants  
Analysis of oil-contaminated specimens was conducted in accordance with the standard for soil contamination test (KS M ISO 16703 [10]). For pretreatment of the specimen, anhydrous Na\({}_{2}\)SO\({}_{4}\) was placed in the oil-contaminated soil (10 g) to maintain the specimen in powder state, and 100 mL of dichloromethane (CH\({}_{2}\)Cl\({}_{2}\)) was added. Extraction was repeated twice for 3 min using ultrasonic wave, dichloromethane obtained through the filter was concentrated to 2 mL, and 0.3 g of silica gel was added and mixed for 5 min to eliminate the impurities. Then, the supernatant was analyzed using gas chromatography [11].  
Analysis of the pattern of total petroleum hydrocarbon (TPH) contained in the soil was carried out using gas chromatography (Agilent Technologies, 7890 A GC System). The column used was Ultra-2 (DB-1, 10 m \(\times\) 0.10 mm \(\times\) 0.10 micron). The initial temperature was set to 50 \({}^{\circ}\)C for 2 min and then increased to 320 \({}^{\circ}\)C at a rate of 8 \({}^{\circ}\)C/min; the specimen was kept at the final temperature for 10 min. The carrier gas was He (1.0 mL/min).  
Heavy metals, such as zinc, nickel, cadmium, copper, arsenic, mercury, lead and hexavalent chromium, were analyzed according to the inductively coupled plasma-mass spectrometry method announced by Ministry of Korean Environment [5]. As shown in Table 2, mercury content was 21.63 mg/kg, exceeding the concern level (20 mg/kg), and TPH of oil contaminant was 21,081 mg, which was 10 times the allowed limit of 2000 mg/kg.
# A Review of Wireless Positioning Techniques and Technologies: From Smart Sensors to 6G
## 3 Wireless Technologies
### Cellular  
The cellular technologies consist of distributed cells and the receivers are served by at least one fixed location transceiver. Each cell utilizes a different set of frequencies, aiming to reduce interference and provide guaranteed quality of service. The cellular-based technologies are commonly used for transmitting voice, data, and multimedia.
## 2 Proposition of EBSMC
For the final implementation, substituting (19) into (6), the integral type control effort for the original second order system can be represented as:  
\[u=-\hat{\sigma}_{2}e_{2}+\hat{\sigma}_{2}\dot{x}_{d}+\hat{M}\ddot{x}_{d}-\hat {M}\int_{0}^{t}\big{(}\dot{u}_{Ceq}-w\text{sgn}(S)\big{)}d\tau \tag{21}\]  
Represent (21) in the form of error states:  
\[u=\hat{M}(1+k_{1}k_{2})e_{1}+\hat{M}(k_{1}+k_{2})e_{2}-\hat{\sigma}_{2}e_{2}+ \hat{\sigma}_{2}\dot{x}_{d}+\hat{M}\ddot{x}_{d}+\hat{M}w\int_{0}^{t}\text{sgn} (S)d\tau \tag{22}\]  
Further, substitute (22) into (4); it results:  
\[ \begin{array}{ll}\dot{e}_{2}&=-\frac{\hat{\sigma}_{2}}{M}e_{2}-\frac{1}{M}u+ \frac{\hat{\sigma}_{2}}{M}\dot{x}_{d}+\ddot{x}_{d}+\frac{1}{M}F_{B}\big{(} \kappa,\dot{\kappa}\big{)}\\ &=-\frac{\hat{\sigma}_{2}}{M}e_{2}-\frac{1}{M}\big{[}\hat{M}(1+k_{1}k_{2})e_{1 }+\hat{M}(k_{1}+k_{2})e_{2}-\hat{\sigma}_{2}e_{2}+\hat{\sigma}_{2}\dot{x}_{d}+ \hat{M}\ddot{x}_{d}+\hat{M}w\int_{0}^{t}\text{sgn}(S)d\tau\big{]}\\ &+\frac{\hat{\sigma}_{2}}{M}\dot{x}_{d}+\ddot{x}_{d}+\frac{1}{M}F_{B}\big{(} \kappa,\dot{\kappa}\big{)}+\frac{1}{M}d\\ &=-(1+k_{1}k_{2})e_{1}-(k_{1}+k_{2})e_{2}+\widetilde{D}(e_{2},\dot{x}_{d}, \ddot{x}_{d},u_{C},F_{B}\big{(}\kappa,\dot{\kappa}\big{)},d)-w\int_{0}^{t} \text{sgn}(S)d\tau\end{array}  \tag{23}\]  
From (17), the sliding mode dynamics can be represented as:  
\[S=\dot{e}_{2}+(k_{1}+k_{2})e_{2}+(1+k_{1}k_{2})e_{1}=\widetilde{D}(e_{2},\dot{ x}_{d},\ddot{x}_{d},u_{C},F_{B}\big{(}\kappa,\dot{\kappa}\big{)},d)-w\int_{0}^{t} \text{sgn}(S)d\tau \tag{24}\]  
**Remark 1**. : _According to (20), the robust gain \(w\) can be applied to maintain the sliding motion even when the system is subject to disturbances. This reveals that the lumped perturbation \(\widetilde{D}\) in (24) can be compensated by the nonlinear integral action, and thereby, the exponential stability of the system can be achieved by a proper choice of gain \(k_{2}\) and \(k_{1}\) used in (22)._  
**Remark 2**. : _The closed-loop system robustness against system uncertainties, as well as unknown exogenous disturbances is achieved by a suitable adjustment of a single robust gain \(w\). When an insufficient large value is applied, the condition (20) may not be attained. Under this circumstance, for example, a critical case that \(w\) = 0, one has \(\dot{e}_{2}+(k_{1}+k_{2})e_{2}+(1+k_{1}k_{2})e_{1}=\widetilde{D}\). Roughly speaking, the closed-loop system is stable by means of bounded-input bounded-output stability (BIBO). In the Appendix A, robust gain estimation and the robust stability issue are going to be addressed further. Based on the achievement of robust stability, one can increase the value of \(w\) gradually to achieve desired control performance without inducing unstable behavior._
# Null Subcarrier Index Modulation in OFDM Systems for 6G and Beyond
## 3 Index Modulation for OFDM Systems
The receiver then uses the combinadic ranking algorithm to extract the corresponding decimal number of the data conveyed by the indices [29].
## 3 Related Work
### Main Services of the Proposed Systems  
The analyzed systems primarily target three user groups: victims, rescuers (or first responders), and administrators, who are typically assumed to have basic to intermediate digital skills. The core functionality of these systems is indoor location tracking. Works such as [11; 12; 13; 14; 15; 16; 17; 18; 19; 20; 21; 23; 24; 25] determine victim locations via mobile applications and display them on building plans accessible to rescuers. Additionally, systems in [13; 15; 16; 18; 25] provide victims with routes to the nearest exits. In [13; 18], victims can request assistance from rescuers during emergencies. The system in [18] also offers illustrated or audio-based guides to address personal emergencies or assist others, covering scenarios like heart attacks, bleeding, difficulty breathing, and fractures. The work in [11] introduces a context-aware victim assessment system using mobile sensors, questionnaires, and passive monitoring. From the analysis of these systems [11; 12; 13; 14; 15; 16; 17; 18; 19; 20; 21; 22; 23; 24; 25], the main services identified include recording RSSI data for Wi-Fi and Bluetooth networks (for fingerprinting), indoor location tracking, guiding victims to exits, assessing health statuses, generating emergency reports, and enabling help requests. However, none of these systems comprehensively address the full spectrum of the requirements outlined by civil protection programs for earthquake scenarios [5; 6; 7; 8].
## 2 Monitoring of Nutritional Status in CKD Patients: Affected Parameters
### Bioelectrical Impedance Analysis  
Bioelectrical impedance analysis (BIA) is a method used to measure body composition based on the rate at which an electrical current travel through the body [52]. Electrical impedance is based on reactance which measures body cell mass, and resistance which measures total body water (TBW), with these two parameters being applied to calculate the phase angle (A). Based on BIA measurement, a number of body composition parameters can be estimated, including body cell mass (ECM), fat mass (FM), muscle mass MM), free fat mass (FFM), and total, intracellular and extracellular body water (TBW, IBW, EBW). BIA however generally tends to overestimate muscle mass, although A appears to be a useful bioelectrical marker in predicting and monitoring nutritional status in HD patients [53; 54]. This important issue should be addressed when using BIA for clinical and research purposes. To better validate BIA, the equations generated to facilitate estimation of muscle mass based on factors including age, sex, height, weight, and lack of one or more should be taken into account. Monitoring of patients' hydration status and weight gain in the interdialytic interval is fundamental. BIA measurements should therefore be taken once dry weight or ideal weight is purported to have been reached, where possible at least 30 min after dialysis and following urination [55; 56]. Indeed, the HD population studied displayed a worsening of intracellular dehydration, hypervolemia and cell mass wasting [22], all of which may potentially result in a reduction in muscle mass and strength. Furthermore, in overweight and obese HD patients, BIA-derived FFM, BCM and A are significantly lower compared to normal-weight patients and BMI-matched controls. Finally, A adjusted for excess fluid after HD, age, and gender, may constitute the most potent predictor of malnutrition and survival in hemodialysis patients [57].
## 3 Results and Discussion
### Thermal Analysis of Wax3D  
The DSC is one of the most effective analytical tools for wax and other polymer materials that helps to identify thermal properties such as melting point and glass transition temperature. A DSC curve shown in Figure 3 for the Wax3D filament indicates the presence of a melting range starting at 46 and ending at 130 \({}^{\circ}\)C. This is most probably due to the fact that the Wax3D represents a blend of different waves. Nevertheless, a distinguishable peak can be observed at 110 \({}^{\circ}\)C. It is interesting to note that the Taguchi optimization method results have shown the printing temperature of 110 \({}^{\circ}\)C to be an optimal value for better dimensional accuracy. In addition, it is evident that such broad melting point ranges are similar to those found in polyethylene-based waxes [20]. Thus, a high probability exists that the Wax3D has polyethylene in its content. Polyethylene waxes can have higher hardness and melting points depending on the crystallinity level, according to [PERSON] [20].  
The TGA weight loss curve is presented in Figure 4. The temperature of 0.5% material decomposition at 327.2 \({}^{\circ}\)C for Wax3D is shown in Table 8. A non-apparent two-stage degradation pattern is observed, and the degradation start of low molecular weight components can be identified during the first step of degradation. From the analysis results, the wax filament may be polyethylene-based synthetic composite wax due to similarities found in the works of [PERSON] et al. [21] and [PERSON] [20]. For example, [PERSON] performed DSC analyses on several commercial HDPE waxes and found melting temperature ranges that are very close to what was found in the current research.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Source** & **Degree of Freedom** & **Sum of Squares** & **Mean Square** & **F** & \(p\) & **Contribution, \%** & **R-sq. \%** \\ \hline Nozzle temperature & 2 & 643.15 & 321,576 & 43.66 & 0.022 & 88.3 & \\ Layer thickness & 2 & 38.52 & 19,259 & 2.61 & 0.277 & 5.3 & \\ Extrusion velocity & 2 & 32.16 & 16,082 & 2.18 & 0.314 & 4.4 & 97.98 \\ Residual Error & 2 & 14.73 & 7365 & & & 2 & \\ Total & 8 & 728.57 & & & & 100 & \\ \hline \hline \end{tabular}
\end{table}
Table 7: ANOVA results for part’s width accuracy.  
Figure 3: DSC curve for Wax3d filament.
## 3 Performance Analysis of TDOA Method and Beamforming Method Based on the Simulated Signals  
Since the finite element simulation signal is close to the actual AE signal and easy to operate, this paper uses the simulation signal to study the performance of TDOA method and beamforming method for localizing AE source.
###### Abstract  
Low Earth orbit (LEO) satellites offer a revolutionary potential for positioning, navigation, and timing (PNT) services due to their stronger signal power and rapid geometric changes compared to traditional global navigation satellite systems (GNSS). However, dedicated LEO navigation systems face high costs, so opportunity navigation based on LEO satellites is a potential solution. This paper presents an orthogonal frequency division multiplexing (OFDM)-based LEO navigation system and analyzes its navigation performance. We use 5G new radio (NR) as the satellite transmitting signal and introduce the NR signal components that can be used for navigation services. The LEO NR system and a novel zero-padding correlation (ZPC) are introduced. This ZPC receiver can eliminate cyclic prefix (CP) and inter-carrier interference, thereby improving tracking accuracy. The power spectral density (PSD) for the NR navigation signal is derived, followed by a comprehensive analysis of tracking accuracy under different NR configurations (bandwidth, spectral allocation, and signal components). An extended Kalman filter (EKF) is proposed to fuse pseudorange and pseudorange rate measurements for real-time positioning. The simulations demonstrate an 80% improvement in ranging precision (3.0-4.5 cm) and 88.3% enhancement in positioning accuracy (5.61 cm) compared to conventional receivers. The proposed ZPC receiver can achieve centimeter-level navigation accuracy. This work comprehensively analyzes the navigation performance of the LEO NR system and provides a reference for LEO PNT design.  
low Earth orbit (LEO); new radio (NR); OFDM; navigation; navigation receiver; integrated communication and navigation 2020 IEEE/RSJ International Conference on Intelligent Systems (IEEE)
# Risk Assessment of Soil Heavy Metals in the Jiahe River Basin of Yantai City, China
## 2 Materials and Methods
### Analytical Methods  
All chemical analyses were performed at the analysis and testing laboratory of the Yantai Center of Coastal Zone Geological Survey, China Geological Survey. In total, 12 items were analyzed: Cr, Hg, As, Pb, Cd, Cu, Ni, Zn, Co, V, Mn, and pH. The preparation and analysis followed the Specification of Land Quality Geochemical Assessment (DZ/T 0295-2016) [26]. As and Hg were determined using the AFS (atomic fluorescence spectrometry) method, with detection limits of 0.2 ug/g and 5 ng/g, respectively. The pH value was assessed using the ISE (ion-selective electrode) method, with a detection limit of 0.1. Cd, Cr, Pb, Ni, Cu, Zn, Co, V, and Mn were analyzed using the ICP-MS (inductively coupled plasma mass spectrometry) method, with detection limits of 21 ng/g, 2 ug/g, 0.5 ug/g, 0.6 ug/g, 0.6 ug/g, 1.1 ug/g, 0.02 ug/g, 3 ug/g, and 0.2 ug/g, respectively. During the sample analysis, first-grade standard samples (GSS-3 and GSS-13) were utilized to control the analytical quality. The quality of the analytical data, including the analytical methods, detection limits, accuracy, and precision, were all within the requirements outlined in the Specification of Land Quality Geochemical Assessment (DZ/T 0295-2016) [26]. The detection rate was 100%, with accuracy greater than 99.85% and precision exceeding 99.83%.