esa-sceva/satcom-chunk-collection huggingface dataset:
# UAV Detection and Tracking in Urban Environments Using Passive Sensors: A Survey
## 2 UAV Detection and Identification
### RF-Based Detection  
The process of RF-based UAV detection typically involves feature extraction from the received RF signal, followed by comparison of the extracted features with the UAV RF feature database to achieve UAV identification. In recent years, learning-based approaches have gained significant traction in the realm of UAV detection, leading to significant changes in RF-based UAV detection methods. To enhance UAV detection using learned methods, researchers have employed various techniques. Generally, these approaches can be divided into two categories. The first category involves extracting signal features using signal processing methods such as Fourier transform, followed by classification using SVM, decision trees, and other methods [29; 32]. The second category involves applying simple processing to the signal, followed by feature extraction using deep neural networks for UAV signal identification [33; 34; 35; 36; 37]. This section will provide an overview of both traditional RF-based detection methods and deep learning-based approaches for UAV detection. Additionally, commonly used datasets for UAV detection will also be introduced.
###### Abstract  
Satellite laser communication can achieve high-speed, high-precision, and high-security broadband communication without being constrained by the electromagnetic spectrum, which has attracted attention. So, this paper proposes the use of a high-altitude platform (HAP) under anisotropic non-Kolmogorov turbulence to improve the communication performance of the system. Cross quadrature amplitude modulation (XQAM) and hexagon quadrature amplitude modulation (HQAM) are applied to the ground-HAP-satellite (G-H-S) laser communication system. Considering the combined effects of uplink light intensity scintillation, beam wander, and the angle of arrival fluctuation, the G-H-S system's bit error rate (BER) closure expression is derived under the EW distribution. Simultaneously, the relationship between the G-H-S system's signal-to-noise ratio (SNR) and BER under different anisotropic factor u values is simulated and compared with the traditional ground-satellite (G-S) system. The results show that the communication performance of the G-H-S system with HQAM modulation is better. In addition, the effects of the zenith angle, receiving aperture, transmitter beam radius, and beam divergence angle on the BER performance of the system are also studied. Finally, the correctness of the analysis results is verified via Monte Carlo simulation. This research will benefit the design and optimization of satellite laser communication systems.  
satellite laser communication; HAP; anisotropic non-Kolmogorov turbulence; XQAM; HQAM; light-speed drift +
Footnote †: journal: _Photonics_  
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Footnote 0: Copyright** © 2023 by the authors. Liconse MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([[https://creativecommons.org/licenses/py/4.0/](https://creativecommons.org/licenses/py/4.0/)]([https://creativecommons.org/licenses/py/4.0/](https://creativecommons.org/licenses/py/4.0/))).
# Optimizing Weighted Fair Queuing with Deep Reinforcement Learning for Dynamic Bandwidth Allocation
## 5 Results and Analysis
### Experiment 2: Twelve Queues  
The experiment was extended by increasing the number of queues to twelve to evaluate the robustness and scalability of the proposed WFQ DRL-continual approach. This expansion enabled a more comprehensive evaluation of the algorithm's capacity to allocate bandwidth dynamically in a complex network environment. The twelve arrival flows had arrival rates \(\lambda i\) = (0.0713, 0.0563, 0.0840, 0.0395, 0.0879, 0.0873, 0.0631, 0.0453, 0.0257, 0.0869, 0.0407, 0.1420) packets/s, and the interarrival times and service times were generated using a gamma distribution with an SCV of 0.8. The average packet size was assumed to be 1 byte per packet, and the total bandwidth was 1 byte/s. An individual queue has a limited buffer \(K_{1}=K_{2}=\ldots K_{12}=32\) packet. The control policy allocated bandwidth weights to \(w_{1}+w_{2}+\ldots+w_{12}=1\). The number of episodes was 1000, with each episode having a time length of 2000 s. Every 20 s, the agent took action.  
After the random function was performed, \(\lambda_{EWC}\) was obtained as explained in Section 2, running over a range of 1000 episodes to find an optimal \(\lambda_{EWC}\) the FIM was computed every 30 episodes, and \(F_{i}\) were stored with the parameters \(\theta_{i}^{s}\).  
A plot of the run-average reward for SAC with the EWC algorithm in the WFQ continual DRL algorithm is shown in Figure 12. It can be seen that convergence occurs after 200 episodes, and the range of reward fluctuation stabilizes between \(-2.5\) and \(-1.9\), resulting in consistent performance. At the beginning of the reward curve, the agent typically explores different assignment strategies (bandwidth weights) for the queues, resulting in more fluctuation. This means that the controller explores all possible processes of the action it is learning in order to achieve an action that yields benefits. As learning progresses, the agent exploits the probabilities of action, resulting in an increase in the reward curve; the policy then gradually converges toward the optimal allocation bandwidth, reducing the variability in the reward curve.  
\begin{table}
\begin{tabular}{c c c} \hline
**Operation** & **SAC** & **SAC with EWC** \\ \hline Time per step & O (0.004) & O (0.004) \\ \hline Time per episode cost (100 steps) & O (0.4) & O (0.4) \\ \hline Time per 30 episodes & O (12) & O (12.00294) \\ \hline \end{tabular}
\end{table}
Table 6: Experimental time comparison between SAC and SAC with EWC.
# Freshness Monitoring of Packaged Vegetables
## 3 Factors Indicating the Freshness of Packaged Vegetables
### Ethylene Response  
Ethylene (C\({}_{2}\)H\({}_{4}\)) is a natural hormone that stimulates the ripening process in plants. Reducing the oxygen partial pressure while elevating carbon dioxide to appropriate levels inside the package inhibit ethylene production, this was initially demonstrated by [PERSON] [28]. For instance, using O\({}_{2}\) partial pressure of 0.5-5 kPa and CO\({}_{2}\) of 1-5 kPa while keeping the temperature in the range of 0-5 \({}^{\circ}\)C for cabbage reduced the ethylene production and hence prolonged its life [16]. In addition, for broccoli, a reduction in methane production by 20% was obtained when treated with 60% CO\({}_{2}\) and 20% O\({}_{2}\) at 25 \({}^{\circ}\)C [29]. This response for low oxygen pressures can be interpreted by understanding ethylene biosynthesis in plants which was described by Yang cycle, where the conversion of 1-aminocyclopropane-1-carboxylicacid (ACC) enzyme to ethylene is suppressed as this reaction is limited by the oxygen concentration inside the package [28; 29]. A similar effect was noticed when elevating carbon dioxide levels, where both conversion from ACC to ethylene and the biosynthesis of this enzyme were inhibited [18; 28; 30].
# Evaluation of Chronic Kidney Disease Risk Factors after Radical Nephrectomy
## 3 Results
Clinically significant AKI has an impact on postoperative eGFR < 60 mL/min, so we analyzed its risk factors. The clinical and demographic parameters of patients grouped by AKI status are presented in Supplementary Table S2: Clinical and sociodemographic data of AKI status patients after radical nephrectomy. All perioperative and postoperative laboratory data of clinically significant AKI are summarized in Supplementary Table S3: AKI status patients' laboratory data before and after radical nephrectomy. The adjusted multivariable analysis excluded age, BMI, CCI, comorbidities, MetS, intraoperative loss of blood > 500 mL and CT nephrometry result complexity, and identified four significant variables as clinically significant AKI risk factors, including NLR > 3.5 (OR 1.42, CI 1.06-1.88, \(p\) = 0.02), low contralateral kidney CT volume (OR 46.70, CI 3.27-667.94, \(p\) < 0.01), higher preoperative eGFR (OR 1.13, CI 1.05-1.22, \(p\) < 0.001) and longer IOH (OR 1.05, CI 1.01-1.10, \(p\) = 0.01), Figure 7.  
This logistic regression model's ROC analysis showed significant sensitivity of 90.1% with specificity of 66.7% as presented in Figure 8.  
Figure 7: Risk factors of clinically significant AKI after radical nephrectomy. Abbreviations: eGFR—estimated glomerular filtration rate; NLR—neutrophil-to-lymphocyte ratio; CT—computed tomography; R.E.N.A.L—CT nephrometry scoring system.
# Graphene-Enhanced CuW Composites for High-Voltage Circuit Breaker Electrical Contacts
## 2 Materials and Methods
### Ablation Resistance Test  
Full-capacity breaking tests were conducted in 252 kV/63 kA high-voltage circuit breakers using CuW80 contact materials prepared by the experimental process and CuW80 contact materials reinforced by adding graphene to compare the macroscopic morphology changes of the contacts as well as the dimensional changes after the experiments.
# Adaptive Tolerance Dehazing Algorithm Based on Dark Channel Prior
## 4 Comparison and Analysis of Experiential Results
### Quantitative Comparison  
The subjective evaluation uses the naked eye to observe the contrast picture before and after dehazing to judge the effect of it. This method is often susceptible to individual factors, such as the aesthetics and psychology of the observer, and cannot be imported into the computer vision system to achieve more accurate and detailed follow-up analysis. Objective evaluation is more automatic, efficient, and easier to integrate than a subjective evaluation. Therefore, we use objective evaluation methods to further evaluate the various algorithms described in this paper.
## 4 Discussion
### Dissociation of Electrophysiological and Motor Effects  
Surprisingly, the beneficial effects of PAS and PAS/MI interventions on motor function were not associated with significant CSE changes. Furthermore, ShamPAS/MI induced a CSE increase later than the observed motor facilitation. A dissociation of the mechanisms underlying such effects, which could rely on different cerebral substrates, seems to exist and has already been suggested [52]. In the [PERSON] study [52], greater improvement in motor performance in the 'physical training' group compared to the 'MI training' group was not found to be associated with a greater difference in CSE. This dissociation could be explained by the limitations of TMS in identifying subtle neural changes that may cause differences in motor performance [52], the variability of the MEP responses and that of the responses to NIBS [53; 54], and/or by the fact that CSE inferred from MEP measurements could primarily reflect fast monosynaptic CSE changes. In humans, the fast monosynaptic pathways of the corticospinal tract (CST) are the most-developed fiber pathways [55]. Phylogenetically, these pathways are fundamental for fine and fast independent finger movements [56]. Numerous studies have pointed out that motor recovery after stroke was only possible with sufficient preservation of the CST [57], especially for fine independent finger movements [58]. However, it represents a limited portion of all the corticospinal motor tract fibers [55], and some recent studies have suggested that other tracts might have a role in poststroke motor recovery although their role remains limited compared to that of the CST [59; 60; 61]. Moreover, the degree of preservation of the corticospinal pathways required for good motor recovery also depends on the residual possible interactions between M1, connected to motoneurons through fast corticospinal pathways, and the premotor cortex, which is not connected monosynaptically to the motoneurons. This interaction indirectly suggests an action on motoneurons through alternate motor tracts [62]. Therefore, the dissociation that we observed between the improvement of motor abilities and unchanged MEPs at the group level is in favor of the idea that MEP could be a tool to assess fast monosynaptic corticospinal projections but does not allow the identification of specific changes in relation to nonmonosynaptic pathways. On the contrary, the improvement in active extension movements observed particularly with the PAS intervention indirectly suggests that the mechanism of PAS might also involve alternate motor tracts, at least in poststroke patients. The absence of synergistic effects between PAS and MI emphasizes the fact that the combination of different rehabilitation interventions cannot be reduced to a simple summation of their effects, and further work is necessary to effectively combine interventions in neurorehabilitation [63].
## 3 Results
### Pressure Fluctuation  
We achieved a transient simulation that captures the pressure fluctuation in the ATH. Figure 5 presents the instantaneous pressure fluctuation, \(P-\overline{P}\), surrounding the ATH head, which represents the acoustic field. It should be noted that the head body of the ATH was fully included in the computational domain, and its shielding effect was accounted for in the simulation. The contours reveal that the primary noise source is located at the front of the ATH, where concentrated pressure fluctuations occur. The pressure fluctuation magnitude is within 100 Pa (ranging from \(-40\) to 40 Pa), approximately 100 times smaller than the dominant pressure generated by the rotational speed at the airfoil tip of the impeller.  
Figure 4: Velocity magnitude distribution inside the air turbine handpiece, showing the airflow behavior across critical regions of the turbine. (**a**) Detailed view of the gap between the impeller and head body; (**b**) cross-sectional view at the inlet plane showing high-velocity airflow entering the first stage of the blades of the impeller; (**c**) cross-sectional view at the outlet plane displaying the deceleration of airflow after interacting with the second stage of the blades.  
Figure 5: Instantaneous pressure fluctuation contours in the acoustic field around the air turbine handpiece (ATH). The simulation model includes the head body of the ATH.
## 1 Introduction
### Background  
Most of the existing works in mobile crowd sensing use different measures to improve the quality of sensing in unpredictable environmental conditions such as spatio-temporal aspects, selection of right participants, selfishness of participants, lack of infrastructure, etc. The different applications require different levels of quality expectations. In order to fulfill these qualities for various applications, we introduced a new concept with more relevant parameters such as such as reliability based on distance \(R_{bd}\), transmission range to sink \(T_{tt}\), time that requires to send to sink/destination \(T_{tt}\), and quality of sensor devices used in mobile devices \(M_{qs}\). These parameters introduce remarkable QOI in crowd sensing for various applications using the opportunistic transmission paradigm.
###### Abstract  
To investigate the influence of the in situ stress on the damage characteristics and fracture patterns of sandstone, this study designed a confining pressure loading device that simulates a deep high in situ stress environment. It allows for the coupled loading of blasting stress and in situ stress on rock specimens. Based on this, experimental research on three-dimensional rock blasting was conducted. A segmental analysis method was then applied, dividing the sandstone into stemming, charge, and bottom segments to refine the study. Using CT scanning, three-dimensional reconstruction, multifractal methods, and SEM scanning technology, the damage characteristics and failure modes of sandstone under the coupling of blasting stress and in situ stress were investigated from macroscopic, mesoscopic, and microscopic perspectives. The experimental research indicates that, under in situ stress, the rock's ability to resist the effects of blasting stress waves and blasting gas is enhanced. With increasing in situ stress, the overall damage level of sandstone specimens gradually decreases and the damage characteristics in different segments of the specimen show significant variation. Under the same in situ stress, the damage level of the sandstone specimen decreases as the axial position shifts from the stemming segment to the charge segment, and then to the bottom segment. Additionally, with increasing in situ stress, shear fractures increase, the blasting fracture surfaces become progressively rougher, and the microscopic fractures in the sandstone transition from brittle cleavage fractures to brittle-plastic quasi-cleavage fractures. In some areas, the energy is insufficient to penetrate the grain boundaries, leading to a transition from transgranular fractures to coupled fractures and intergranular fractures.  
blasting; deep rock mass; in situ stress; damage; fracture; fracture morphology +
Footnote †: journal: Applied sciences  
Article
## 6 Simulation and Experiment of Weak Signal Detection Using Double-Coupled Duffing System
### Simulation Study of Single-Component Noisy Signal Detection
The traditional Holmes-Duffing system and the double-coupled Duffing system established in this article were tested separately, and the recognition rate varies with the amplitude of the periodic signal in the tested signal as shown in Figure 8.  
Observing Figure 8, the recognition rate of the method proposed in this paper is significantly better than that of the traditional Holmes-Duffing system. After calculation, the minimum signal-to-noise ratio that the traditional Holmes-Duffing system can detect is -20.80 dB. Via this analysis, it is shown that the double-coupled Duffing system established in this article has a 2.96 dB decrease in the minimum signal-to-noise ratio that can be detected compared to the Holmes-Duffing system, and it has better detection performance. Figure 8: Recognition rate variation chart. Figure 7: Box graph of output value variance of double-coupled Duffing system.
# Phishing Attacks Survey: Types, Vectors, and Technical Approaches
## 3 Phishing Methods and Techniques
### Phishing Vectors
#### 3.2.2 Smishing  
The medium of SMS/MMS is responsible for the vector of smishing. This is the use of the short messaging service to implement phishing attacks. There are two main approaches using this methodology. The first method involves sending a SMS pretending to be a trusted authority (such as a bank, etc.) containing a vital message, e.g., regarding the message recipient's identity or theft of banking information. The victim is then directed to a fraudulent website or phone number, which requires the victim to login or provide some identifying information. Once this has occurred, attackers can then use the details they have gathered to their own benefit.  
The other method involves the sending of a text to a victim that either directly contains malware or provides a link to a website that contains malware. Once the malware is installed, the phisher can continue with their attack, which may range from simply stealing the target's contacts and messages, to creating a bot-net or accessing authentication codes for logins or purchases [30; 32].
## 1 Introduction
This control method combines the simplicity and high-precision characteristics of open-loop control and the stability characteristics of closed-loop control. Then, the whole control process of stability, speed, and unity of time and space is realized. From these biological control mechanisms, a novel open-closed-loop control mode is proposed to try to solve the above problems of the feedback control method. To achieve open-closed-loop control, it is necessary to build a control and data acquisition platform to collect real-time UAV state data and continuously control the UAV. In terms of the UAV platform, many researchers have made many research contributions in various aspects [21; 22]. However, the platform of this proposal needs to be improved in many aspects to obtain real-time control instructions and corresponding state data for offline training later. Then, the UAV maneuverability model, which establishes the relationship between control commands and desired accelerations, was built and trained. Because each UAV's maneuverability model is known, the trajectory planning of each UAV can avoid the control boundary crossing problem, and the planned trajectory can be transformed into specific control instructions. Thus, this trajectory tracking strategy in open-loop control mode can improve the internal dynamic oscillation and overshoot problems, and the precise flight trajectory reproduction on the unity of time and space can be realized. The main contributions of this paper mainly consist of two parts. Firstly, a real-time control and acquisition platform with high-precision positioning, low-delay communication, and asynchronous distribution was built to collect the UAV real-time flight data and control the quadrotors asynchronously. A high positioning accuracy of \(\pm 15\) cm was realized with the support of the multi-sensor fusion technique, and the transmission delay of wireless communication was only 3.0\(\sim\)3.5 ms by adopting a double-data-link structure. Secondly, a novel control strategy for quadrotor trajectory tracking is proposed. As the key part of the control strategy, the maneuverability model is presented to bridge between the control commands and the desired acceleration. Then, the combined control mode on the PID closed-loop and the open-loop on the LSTM maneuverability model was determined and verified. The experimental results show the good consistency between the preset and actual speeds of the UAV when the proposed control model is used. The hybrid control strategy, which combines the high-precision characteristics of open-loop control and the stability characteristics of closed-loop control, can effectively reduce the system oscillation and overshoot that often occur in closed-loop and nonlinear control methods. The rest of this paper is organized as follows. Section 2 describes the method, which involves the compound control method, maneuverability model, and high dynamic platform. In Section 3, the results of the platform, model, and flight experiments are shown and estimated. Finally, Section 4 illustrates the conclusions.
## 2 Dispersive Fourier Transformation Technique
### Theory of DFT
#### 2.1.3 Near-Field Condition  
In normal DFT process as outlined above, a significant amount of chromatic dispersion is required to satisfy the temporal far-field condition. The optical pulse that propagates through the dispersive medium will be fully stretched, making the time-encoded spectral features slowed down and easily captured in time-domain. However, highly dispersive media could cause significant signal losses, especially outside the telecommunication band. In addition, the substantial dispersion demand imposes a strong physical limit on the maximum update speed of DFT-based system and reduces the overall achievable time-bandwidth-product (TBWP) of the system.  
Some research efforts have been dedicated to study relaxed dispersion requirement for far-field DFT [37] and its application in chirped microwave waveform generation [57]. A further study shows that even in the near-field region the spectral information can be reconstructed from two separate temporal measurements using off-line processing [58]. In [59], near-field DFT has been investigated for generating high fidelity microwave waveforms, which is made possible by pre-distorting the optical pulse before stretching.