esa-sceva/satcom-chunk-collection huggingface dataset:
# Device Free Detection in Impulse Radio Ultrawide Bandwidth Systems
## 4 Device Presence Modelling  
In this section, the mean and variance are calculated when the device is present. This will later be used for designing the Neyman-Pearson criteria. First, the characteristic function (CF) is determined, followed by its moments. With known moments, the mean and variance can be easily calculated. Furthermore, the CF can help measure higher order moments which will help in determining the kurtosis, which can be used for determining the shape of the density as mentioned in [57].
# Study on the Anti-Interference Performance of Substrate-Free PEDOT:PSS ECG Electrodes
###### Abstract  
Abstract: Substrate-free electrodes are promising dry electrodes for long-term physiological electrical signal monitoring due to their ultra-thinness, conformal contact, and stable skin-electrode impedance. However, the response of substrate-free electrodes to various disturbances during electrocardiogram (ECG) monitoring and the corresponding optimization needs to be investigated. This paper investigates the specific effects of various influencing factors on skin-electrode impedance and ECG during electrocardiogram (ECG) detection. The research utilizes substrate-free poly(3,4-ethylenedioxythiophene)/poly(styrene-sulfonate) (PEDOT:PSS) electrodes. The investigation employs several methods, including skin-electrode impedance comparison, ECG waveform analysis, spectrum analysis, and signal-to-noise ratio (SNR) evaluation. To avoid the impact of physiological state differences in subjects at different times, relevant data were only compared with the same group of experiments conducted in the same period. The results demonstrate that the substrate-free conformal contact PEDOT:PSS electrode has more stable skin-electrode impedance and could obtain a more stable ECG than partial contact electrodes (the SNR of the partial contact and conformal contact electrodes are 1.2768 \(\pm\) 4.0299 dB and 7.2637 \(\pm\) 1.4897 dB, respectively). Furthermore, the ECG signal quality of the substrate-free conformal contact PEDOT:PSS electrode was independent of the electrode area and shape (the SNRs of the large, medium, and small electrodes are 4.0447 \(\pm\) 0.4616 dB, 3.9115 \(\pm\) 0.5885 dB, and 4.1556 \(\pm\) 0.5557 dB, respectively; the SNRs of the circular, square, and triangular electrodes are 9.2649 \(\pm\) 0.6326 dB, 9.2471 \(\pm\) 0.6806 dB, and 9.1514 \(\pm\) 0.6875 dB, respectively), showing high signal acquisition capability that is the same as microneedle electrodes and better than fabric electrodes. The results of clothing friction effects show that skin-electrode impedance stability was important for ECG stability, while the impedance value was not (the SNRs of friction and non-friction electrodes are 2.4128 \(\pm\) 7.0784 dB and 9.2164 \(\pm\) 0.6696 dB, respectively). Moreover, the skin-electrode impedance maintains stability even at a high breathing frequency, but the ECG signal fluctuates at a high breathing frequency. This experiment demonstrates that even when the skin-electrode impedance remains stable, the ECG signal can still be susceptible to interference from other factors. This study suggests that substrate-free PEDOT:PSS that could form conformal contact with the skin has higher skin-electrode impedance stability and could measure a high ECG signal even with a small electrode area, demonstrating its potential as dry ECG electrodes, but the interference from other physiological electrical signals may require better circuit design.  
substrate-free electrode; PEDOT:PSS electrode; skin-electrode impedance; ECG; anti-interference +
Footnote †: journal: Applied Physics Letters
# Energy-Efficient BWP Configuration for Multi-Slice Users
## 7 Conclusions  
This paper proposes a savvy and flexible scheme to select an appropriate BWP configuration for users connected to multiple slices that help such users reduce their energy consumption without hindering their QoS. The BWP configuration selection between multi-numerology and single-numerology BWPs is assessed for each user depending on multiple factors, including battery level and QoS satisfaction. Two approaches are adopted. The first approach is a centralized one based on a global optimization problem where a central entity minimizes the total cost of users by selecting for each user the most adequate BWP configuration. The second approach is a distributed one based on non-cooperative game theory, where each user selects autonomously the BWP configuration that minimizes its own cost. Extensive simulations prove the efficiency of our devised scheme against the static legacy scheme, and our evaluation of the price of anarchy proves the precedence of the distributed approach over the centralized one, as it combines fast convergence and near optimal performances.  
For future work, we intend to take into account additional services for users connected to multiple slices.  
Conceptualization, J.S.; software, J.S.; validation, J.S.; formal analysis, K.K.; writing--original draft preparation, J.S.; writing--review and editing, K.K., M.Y. and S.C. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
Data Availability Statement: Data will be made available upon request.  
The authors declare no conflicts of interest.
## 5 Implementation and Simulations
### Network Performance Evaluation  
For the purpose of evaluation, we use the following network metrics in our study:  
* Packet delivery ratio: This is the ratio between the amount of data packets received and the amount of data packets sent. The packet delivery ratio can also be interpreted as the ratio of the number of packets received at the constant bitrate (CBR) sink to the number of packet sent by the CBR source.
* Routing overhead: This is defined as the total number of routing control packets transmitted.
* Throughput: Network throughput refers to the average data rate of successful data or message delivery over a specific communications link.
* End to end delay: The end to end delay of a packet is defined as the time a packet takes to travel from the source to the destination.
# Electricity Losses in Focus: Detection and Reduction Strategies--State of the Art
## 3 Methods for Identifying Power Losses  
### Technical Energy Losses  
In the context of technological advancements across various disciplines, including the electrical field, researchers have demonstrated a notable interest in this area. Consequently, research efforts have been undertaken from diverse perspectives, encompassing studies on energy losses, their manifestation in power systems, loss mitigation, primary causes, and numerous other related subjects. The technical energy losses are more readily quantifiable due to the physical elements and phenomena that give rise to these losses. Conversely, the identification of non-technical energy losses is more challenging, necessitating the implementation of more complex solutions for their reduction.  
Given that researchers have utilized a multitude of methods to identify electricity losses, a variety of programs and applications have been developed to determine these losses. The research carried out in this field is extensive and is divided into several branches, thus approaching the field of electro-energetics from multiple perspectives.  
As can be seen in Figure 3, the quantification of technical losses in power systems is underestimated by the dominant categories of scientific papers. The graph has been constructed using the database provided by Scopus, a comprehensive source of scientific research since the advent of electricity. Therefore, the main categories of scientific research have been recorded and quantified according to their number, and this ranking has been analyzed in detail.  
As shown, the predominant contributions to this area of interest were scientific articles in journals, accounting for 52.5%, followed by research papers at conferences, accounting for 37.4%, and chapters in textbooks and other categories of interest. It is evident that the field of electricity losses is currently experiencing a growth in interest.
## 2 Object Detection
### Regression-Based Object Detectors (One-Stage Detectors)
#### 2.4.5 CornerNet  
[PERSON] et al. [48] implemented CornerNet for object detection, wherein the object is detected by a pair of key points using a CNN instead of drawing an anchor box around the detected object. So the need for designing anchor boxes usually used in one stage detectors is eliminated by detecting objects as paired key points; i.e., top-left and top-right corners respectively. They introduced a new type of pooling layer referred to as corner pooling, which helps the network to localize corners better. The CNN outputs the heatmap for all top-left corners and bottom-right corners, along with an embedded vector map for each detected corner. On the MS-COCO dataset, CornerNet achieved 42.2% AP which outperforms the existing one-stage detectors. Figure 14 shows the CornerNet architecture. The main drawback is that it generates incorrect paired key points for the detected object. So to overcome this drawback, [PERSON] et al. [49] implemented CenterNet by introducing a third key point at the center to detect each object. CenterNet achieved 47% AP, and inference speed is slower than CornerNet. Table 1 shows the summary of different object detection algorithms tested on Pascal Titan X GPU on MS-COCO and Pascal-VOC2007 datasets. Table 2 shows a comparison of various deep learning-based object detectors' performances on the MS-COCO test-dev dataset.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**S.No**} & \multirow{2}{*}{**Architecture**} & **mAP** & **mAP** & \multirow{2}{*}{**FPS**} \\  & & **(MS-COCO)** & **(Pascal-Voc 2007)** & & \\ \hline
1 & RCNN [17] & – & 66\% & 0.1 \\
2 & SPPNet [32] & – & 63.10\% & 1 \\
3 & Fast RCNN [33] & 35.90\% & 70.00\% & 0.5 \\
4 & Faster RCNN [2] & 36.20\% & 73.20\% & 6 \\
5 & Mask RCNN [44] & – & 78.20\% & 5 \\
6 & YOLO [40] & – & 63.40\% & 45 \\
7 & SSD [41] & 31.20\% & 76.80\% & 8 \\
8 & YOLOv2 [42] & 21.60\% & 78.60\% & 67 \\
9 & YOLOv3 [43] & 33.00\% & – & 35 \\
10 & SqueezeDet [45] & – & – & 57.2 \\
11 & SqueezeDet+ [45] & – & – & 32.1 \\
12 & CornerNet [48] & 69.2 & – & 4 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Summary of different object detection (Pascal Titan X GPU) performances on MS-COCO and Pascal-voc07.  
Figure 13: SqueezeDet architecture [45].
## 3 Results and Discussion  
### Nugget Size and Tensile Shear Strength  
Table 3 lists the nugget size and tensile shear strength values of the resistance spot welds obtained using two different electrodes. When the as-received electrode was used, nuggets with sizes 7.2 mm and 8.2 mm were formed at the electrode forces of 400 kgf and 600 kgf, respectively; thus, the nugget size was slightly larger at the electrode force of 600 kgf. On the other hand, when the abraded electrode was used, nuggets with sizes 7.04 mm and 6.90 mm were formed at the electrode forces of 400 kgf and 600 kgf, respectively. Thus, comparatively larger nuggets were formed when the as-received electrode was used. The tensile shear strengths of the welds obtained with the as-received electrode were 4.99 kN and 4.89 kN at 400 kgf and 600 kgf, respectively. Even when including the error, the difference could be considered negligible. On the other hand, when the abraded electrode was used, welds with tensile shear strengths 4.37 kN and 4.23 kN were produced at 400 kgf and 600 kgf, respectively. Compared to the welds produced with the as-received electrode, those produced with the abraded electrode had lower tensile shear strengths. The weld nuggets formed with the as-received electrode were larger than those formed with the abraded electrode; therefore, the tensile shear strengths of the welds obtained using the as-received electrode were relatively larger.
###### Abstract
According to the integrated study of ranging communication for space gravitational wave detection by [PERSON] [11], if the PRN (bipolar) is unbalanced (i.e., this means that in the sequence, the number of binary values \"1\" and \"\(-1\)\" is not equal, resulting in an imbalance in their occurrences) or remains unbalanced after combining with data, it will generate a DC component during BPSK modulation, leading to main lobe noise. This will affect the tracking accuracy of the phase signal and cause errors in the ranging accuracy [11]. Currently, both domestically and internationally, there is limited research on noise issues caused by the balance of PRN codes [12; 13]. Therefore, this paper analyzes the impact of the balance of PRN codes and presents a method for generating a bit-balanced PRN code that ensures balance in PRN codes of any length occupied by data. Next, core parameters, such as odd-even autocorrelation/cross-correlation functions and maximum spectral amplitude, are used to construct the evaluation criteria. By employing models such as divide-and-conquer path planning and the maximum clique model, the bit-balanced ranging pseudocode sequence with the best overall performance is selected. The method proposed in this paper can effectively eliminate the impact of DC phase noise caused by BPSK modulation, enhancing the robustness of inter-satellite ranging communication in space gravitational wave detection, thereby meeting the requirements for high-precision and high-reliability communication. Meanwhile, this paper provides new ideas and methods for ranging communication coding designs in this field. The structure of the content of this paper is arranged as follows:  
Chapter 2 will provide a detailed analysis of the phase noise caused by BPSK modulation. Through theoretical derivation and mathematical modeling, it will determine the main lobe and sidelobe noise levels in BPSK modulation, aiming to reveal the significant impact of BPSK phase modulation on system noise and emphasize the necessity of optimization in the design;Chapter 3, in order to suppress the noise caused by BPSK phase modulation, proposes a BBC sequence design and optimization method based on Weil sequences. This method ensures bit balance in PRN sequences of any length during the data encoding process, effectively eliminating the impact of the DC component;  
Chapter 4 compares the optimized BBC sequence with the original Weil sequence based on performance indicators, such as odd/even autocorrelation, odd/even cross-correlation, and maximum spectral amplitude. It also analyzes the DC component after modulating the BBC sequence. Through these comparisons, the effectiveness of the optimized BBC sequence design is validated;  
In the final chapter, this paper summarizes the research work and discusses the current limitations and future research directions.
# Making Sense of Machine Learning: A Review of Interpretation Techniques and Their Applications
## 3 Techniques for Explainable AI
### Post Hoc Interpretation Techniques
#### 3.4.2 Gradient-Weighted Class Activation Mapping  
Grad-CAM [23] was proposed by [PERSON] et al. for producing visual explanations for convolutional neural network (CNN)-based models. It uses the gradients of a target concept to produce a localization map and highlights the important regions in the image for the corresponding prediction. Furthermore, [PERSON] et al. [59] discussed how Grad-CAM was used to generate visual explanations for the decision-making process of a deep learning model trained on image classification. The generated explanations helped to improve the model's robustness to adversarial attacks.  
[PERSON] et al. [60] proposed permutation feature importance (PFI) to measure the decrease in model performance after shuffling a feature's values. A feature is important if shuffling its values increases the model error, because the model relies on the feature for the prediction. In contrast, a feature is not so important if shuffling its values has no or little effect on the model error.
## 3 Results and Discussion
### Thermogravimetric Analysis  
Figure 5a shows TGA plots of the pure poly(St-_co_-MMA) copolymer and poly(St-_co_-MMA)/FA composites with different FA loadings. As shown in the figure, the onset decomposition temperatures of the poly(St-_co_-MMA)/FA composites were increased in comparison with that of pure copolymer, which can be ascribed to the existence of the FA in the composite. The pure poly(St-_co_-MMA) samples had a maximum weight loss temperature of 404 \({}^{\circ}\)C, while the maximum weight loss temperature of the 10 wt.%, 30 wt.%, and 50 wt.% FA composites increased to 410 \({}^{\circ}\)C, 414 \({}^{\circ}\)C, and 417 \({}^{\circ}\)C, respectively (Figure 5b). The increase of the maximum weight loss temperature may be attributed to the heat barrier of FA platelets in poly(St-_co_-MMA). With the increase of FA content, the final weight loss of poly(St-co-MMA)/FA microspheres was lower than that of pure poly(St-_co_-MMA) microspheres; this results illustrates that FA improved the thermal stability of the poly(St-_co_-MMA) matrix [30]. This may be viewed as the good distribution of FA  
Figure 4: Microscope images of (**a**) pure poly(St-_co_-MMA), (**b**) 10 wt.% FA, (**c**) 30 wt.% FA, and (**d**) 50 wt.% FA microspheres.  
Figure 3: The XRD patterns of poly(St-_co_-MMA), poly(St-_co_-MMA)/10 wt.% FA, and poly(St-_co_-MMA)/30 wt.% FA.  
powder and the tortuous path in the hybrid, which hinders the diffusion of the volatile decomposition compared to that in pure poly(St-_co_-MMA). Thus, the incorporation of FA particles within the poly(St-_co_-MMA) copolymer matrix could significantly enhance the thermal stability [24; 31].
## 4 Conclusions  
The task of detecting and localizing a moving target using IR-UWB radar requires a perfect separation of the waves scattered by the time-invariant background from the waves scattered by the moving targets. Subspace learning has proved its capacity to recover the low-rank matrix modeling the clutter signal and the sparse error matrix modeling the target signal.  
In this paper, Robust PCA via the Inexact Augmented Lagrange Multiplier is proposed for clutter removal in IR-UWB-based target detection and localization, and a novel processing mechanism is developed to adapt this batch-oriented algorithm to the real-time processing trend. The algorithm  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & **RPCA (Live)** & **RPCA (Batch)** & **EAM** & **PCA** \\ \hline RMSE & 1.261 & 1.287 & 1.873 & 1.962 \\ Locat. Error (m) & 0.26 & 0.49 & 1.33 & 1.29 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Numeric results for a one-person-scenario.  
\begin{table}
\begin{tabular}{l c c c c} \hline \hline  & **RPCA (Live)** & **RPCA (Batch)** & **EAM** & **PCA** \\ \hline
2 Moving targets & 3.715 & 4.828 & 5.489 & 6.712 \\
3 Moving targets & 3.712 & 4.734 & 5.00 & 6.104 \\
5 Moving targets & 1.397 & 1.346 & 1.576 & 1.958 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Numeric results (RMSE) for a multiple-person scenario.  
Figure 8: Target detection results for 2, 3 and 5 targets-scenarios: column (**a**) O-W processing RPCA, column (**b**) batch processing RPCA, column (**c**) EAM, column (**d**) PCA.  
performs well in simple scenarios as well as in complex ones. The results prove that we can accurately perform the task of detection and localizing a moving target within an online framework.  
This research was supported by the MSIP (Ministry of Science, ICT and Future Planning). Korea, under the ITRC (Information Technology Research Center) support program (IITP-2016-R2718-16-0011) supervised by the IITP (Institute for Information & communications Technology Promotion) in part, and also this work (Grant No. C0351676) was supported by Business for Cooperative R&D between Industry, Academy, and Research Institute funded Korea Small and Medium Business Administration in 2015.  
[PERSON] and [PERSON] conceived the idea and designed the experiments; [PERSON] and [PERSON] developed the libraries required for the radar module and the application interface; [PERSON] and [PERSON] performed the experiments, analyzed the results and wrote the manuscript.  
The authors declare no conflict of interest.
## 3 Results
### Visualization of Salinity Distribution in the Yellow River Delta
In Figure 13a, these areas correspond to herbaceous wetlands, water bodies, and bare/sparse vegetation areas. These observations further confirm that seawater intrusion increases soil salinity, making plant growth difficult. The overall salinity distribution of the region is also evident. Furthermore, we found that the salinity in built-up areas is particularly severe, possibly due to human activities leading to an excess of surface soil salts. There are very few trees planted in the built-up areas of the Kenli region, with most being grasslands, as shown in Figure 13a. Grasslands consume much less water compared to trees, which results in an imbalance in the water cycle. A large amount of water escapes the root zone and percolates down into the groundwater below. The construction of roads, buildings, and other infrastructures also alters the natural drainage pattern, and excess water may come from leaking sewage, rainfall, or water pipes. Over time, the underground water system fills up, bringing dissolved salts along with it. These salts accumulate beneath the surface, eventually leading to the formation of salinized areas. Urban salinization occurs due to the combined effects of excessive water and salt in the environment. Human activities significantly contribute to salinization. In terms of soil type classification, as shown in Figure 13b, the strongly saline and extremely saline areas are predominantly found in saline-alkali soils, which are high in salts, strongly alkaline, and structurally poor, making them unsuitable for plant growth. Non-saline and slightly saline areas correspond to semi-hydrated soils and Entisols. Semi-hydrated soils contain higher moisture levels, though they typically do not reach saturation. The soil moisture is somewhat mobile, which helps dilute the soil salinity. Entisols are newly deposited soils, and as seen in Figure 13b, the flow of the Yellow River through this  
Figure 13: (**a**) Sentinel-2 10 m resolution land use data are from [[https://viewer.esa-worldcover.org/worldcover/](https://viewer.esa-worldcover.org/worldcover/)]([https://viewer.esa-worldcover.org/worldcover/](https://viewer.esa-worldcover.org/worldcover/)) (accessed on 28 October 2024) (**b**) Soil type classification is from the Natural Resources Network [[https://www.resdc.cn/data.aspx?DATAID=145](https://www.resdc.cn/data.aspx?DATAID=145)]([https://www.resdc.cn/data.aspx?DATAID=145](https://www.resdc.cn/data.aspx?DATAID=145)) (accessed on 28 October 2024). region keeps these soils in a dynamic state, where salts are either flushed away or dispersed by the water, thus maintaining non- or slightly saline status.
# Research on Dynamic Modeling and Transition Flight Strategy of VTOL UAV
## 1 Introduction
### Formulation of the Problem  
There are three main flight modes of the UAV: take-off/landing mode, horizontal flight mode and transition flight mode. During the transition, the aircraft configuration changes constantly, and various control units work together to meet the requirements of smooth flight. In this process, the reasonable distribution of power and the reasonable range of speed must be considered, so as to ensure that the lift force of the UAV meets the flight requirements, and the flight attitude in the process is continuously changing. Therefore, transition flight mode is the most complex flight mode of VTOL UAV. In order to ensure the safety of transition flight, it is necessary to determine the transition flight corridor of the aircraft so that the aircraft can safely transition in the transition flight corridor. In addition, theestablishment of the dynamic mathematical model of the variable configuration aircraft, and how to accurately describe its transition flight motion, are also the focus of the study [1; 2; 3].