esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### Experimental Programme
#### 2.3.2 Mechanical Characterization Tests  
For mechanical characterisation, the following tests have been conducted: surface hardness, dynamic modulus of elasticity, flexural and compressive strength, and finally, scanning electron microscopy (SEM).  
Surface hardness, which reflects the resistance of the developed composites to surface scratching, was determined with the help of a Shore C hardness tester [26]. For this purpose, 4 \(\times\) 4 \(\times\) 16 cm\({}^{3}\) samples were used. Five measurements were taken on two faces.  
For dynamic modulus of elasticity determination, a 50 kHz-frequency Matest C368 time ultrasonic machine was used. Once the ultrasound propagation speed waves in samples were obtained, it was determined by means of the following expression:  
\[MOE=\frac{\rho(1+\mu)(1-2\mu)v_{us}{}^{2}}{(1-\mu)} \tag{2}\]  
where \(MOE\) is the modulus of longitudinal elasticity, \(\rho\) is the density of the tested plaster composite, \(\mu\) is the Poisson's ratio of the material, and \(v_{us}\) is the propagation velocity of the ultrasonic wave.  
For flexural and compressive strength tests, samples of 4 \(\times\) 4 \(\times\) 16 cm\({}^{3}\) were used, following UNE-EN-13279-2 standard [31] recommendations. This test was conducted using a hydraulic press model AUTOTEST 200-10 SW from IBERTEST (Madrid, Spain) [45]. First, a three-point bending test was performed on samples using a loading speed of 10 N/s until break. Once the samples were rotated in two parts, they were assessed until failure in the compression modulus of the press, applying a loading speed of 20 N/s.  
Finally, to complete the newly designed composite's mechanical characterisation, a scanning electron microscopy (SEM) study was conducted. The objective of this SEM technique was to understand the mixture behaviour of the HDPE and binder. To conduct these microscopies, a Jeol JSM-820 microscope operating at 20 kV was used; samples were previously coated with a thin layer of gold with a metalliser to ensure the conductivity of the electrons [33].
# Enhancing Unmanned Marine Vehicle Security: A Periodic Watermark-Based Detection of Replay Attacks
## 3 A Periodic Watermark-Based Detection of Replay Attacks  
### Periodic Watermarking Detection Mechanism  
As shown in Figure 5, the attacker intercepts the actual sensor measurement \(y(k)\) and forwards \(y^{\prime}(k)\) to the estimator or controller regularly. Furthermore, it has been shown in [PERSON] et al. [23] that under certain conditions, these attacks can evade detection.  
Figure 4: The timing diagram of the replay attacks.  
Figure 5: UIMVs equipped with periodic watermarking algorithm.  
**Lemma 1**.: _In the scenario where a UMVs system faces a replay attack and equipping with a \(\chi^{2}\) detector, ensuring \(\varepsilon=(A_{dp}+B_{dp}L)(I_{n}-LC)\) is Schur stable implies that the false alarm rate \(\alpha\) and the positive detection rate \(\beta_{k}\) at time \(k\) will equalize over time, confirmed by \(\lim_{k\rightarrow\infty}\beta_{k}=\alpha\)._  
According to Lemma 1, the detector's alarm rate matches the false alarm rate, therefore complicating the confirmation of attacks upon alarms. To combat replay attacks, [PERSON] et al. [31] introduced a technique of continuously adding Gaussian watermark signals \(\Delta o(k)\) into the control inputs. It should be noted that, unless otherwise specified, the continuous watermark referenced hereafter is assumed to be a Gaussian signal. The actual control input can thus be described as:  
\[u^{r}(k)=u(k)+\Delta o(k) \tag{12}\]  
where \(u^{r}(k)\) represents the actual control input of UMVs system added Gaussian watermark signals.  
For UMV systems that are less responsive to watermarking, achieving an adequate detection rate might necessitate significantly increased watermark intensities [PERSON] et al. [30]. To reduce the system control cost, a periodic watermarking mechanism is proposed in Figure 6.  
Compared to the method in [PERSON] et al. [30], the primary advantage of this periodic watermarking method lies in its reliance on comparing the relative magnitudes of the detection functions for compensation signals at various times within the same cycle rather than their absolute values. At time \(k=t_{0}\), a periodic random watermark is introduced into the control variable, and a corresponding compensation signal is designed. As the system operates, this compensation signal develops periodicity that aligns with the watermark's cycle. Furthermore, during each operational cycle of the UMV, there is a direct correlation between the compensation signal and the watermark.
## 4 Results and Discussion
### Spatial and Temporal Distribution of Crop Yields  
Figures 8 and 9 show the yield distribution of maize and sunflower from 2010 to 2015. For maize, most yields fell in the range of 9.23 (the 10 th percentile) to 13.43 t/ha (the 90 th percentile). The maximum maize yield occurred in Hangjinhouqi, which averaged to 11.08 t/ha, while the minimum yield occurred in Dengkou and Wuyuan, which averaged to 10.83 t/ha. Annual average yields from 2010 to 2015 ranged from 10.62 t/ha in 2011 to 11.41 t/ha in 2015. For sunflower, most yields fell in the range of 2.43 (the 10 th percentile) to 5.35 t/ha (the 90 th percentile). The maximum  
Figure 6: Comparisons of statistical and estimated maize production at the county level using models 1 (a), 2 (b) and 5 (c).  
Figure 7: Comparisons of statistical and estimated sunflower production at the county level using models 5 (a), 6 (b) and 8 (c).  
sunflower yield occurred in Wuyuan, which averaged to 3.76 t/ha, while the minimum yield occurred in Dengkou, which averaged to 3.64 t/ha. Annual average yields from 2010 to 2015 ranged from 3.54 t/ha in 2012 to 3.87 t/ha in 2014.  
The yields of maize and sunflower in Dengkou were both the lowest compared with the other three counties. Possible reason for this spatial variation was that there were more lands with sandy soils in Dengkou, which was not conducive to the growth of maize and sunflower. Meanwhile, maize and sunflower both reached their highest yields in their most distributed counties, Hangjinhouqi and Wuyuan, respectively. The more planted percentage of a crop in an area, the more applicable of the crop in the area. In other words, the present maize and sunflower distributions are generally in agreement with the environment adaptability of these two crops.
## 4 Case Study
### Concrete Crack Detection Using the Proposed System
(**a**) clear background, (**b**) dark background, (**c**) blurred boundaries, (**d**) bright background, (**e**) high contrast, (**f**) several cracks. Figure 24: Cracks on the dam pier: (**a**) panorama of the pier, where the red circle is the position of cracks; (**b**) crack with clear concrete background; (**c**) crack with wet and blurred background. The measurement results of the cracks on the pier of the concrete dam are presented in Table 8. Except for two cracks that are undetected, the relative errors are less than 5%, which conforms to the trend of the accurate measurement of large cracks captured at close range. Due to the crack protrusions, the specific error is larger than in the lab, and some errors are more than 0.2 mm. Comparing the crack measurement results in another study [25], the absolute error in this system is a bit larger due to the longer distance and wider width, but the relative errors are similar--most are less than 5% and can satisfy practical application. Figure 26: Original image of the captured crack and the processed result. (**a**) crack No.1 to No.3 on simple background, (**b**) crack with lots of noises, (**c**) crack No.4 and No.5 on simple background, (**d**) crack on uneven plane, (**e**) crack No.6 to No.8 on simple background, (**f**) crack on complex background. Figure 25: Cracks on concrete dam pier with different background and segmentation results. (**a**) narrow crack, (**b**) artificial mark interference, (**c**) boundaries refinement, (**d**) blurry boundaries, (**e**) accurate segmentation, (**f**) artificial mark interference, (**g**) blurry boundaries, (**h**) boundaries refinement. The mathematical model of the proposed camera and laser rangefinder can efficiently measure the unit pixel size, and the improved U-net segmentation algorithm can properly extract cracks. It can be demonstrated that the proposed approach for crack width measurement is verified to be efficient and accurate.
## 4 Representative Machine Learning Models for IONM-Related Research
### Random Forests  
Ensemble learning is a promising technique to improve the accuracy of ML by combining the results of multiple classification or regression models [10; 55]. There are two primary strategies to combine ML models: bagging and boosting. In bagging, the training data are randomly split into overlapping subsets, and each model is trained on one of them. The results of the models are combined by averaging or voting. Random forests are ensemble models that combine decision trees by using the bagging strategy. Decision trees are vulnerable to overfitting [28], which is effectively reduced with bagging [56]. In addition, random forests retain the advantage of decision trees in that they do not require data normalization and are relatively easy to interpret.
## 5 Conclusions  
In this study, the two-electrode method was used to investigate the electrical resistivity characteristics of calcareous sand samples with different size fractions under different conditions, such as temperature, pore water solution, saturation, and relative density. The main research results are as follows:  
1. As the temperature increased, the resistance of the calcareous sand sample gradually decreased, and the relationship between temperature and resistance was approximately linear. For calcareous sand with size fractions of 1-1.5 mm, 1.5-2 mm, and 2-2.5 mm, the resistivity decreased by 0.48 \(\Omega\cdot\)m, 0.94 \(\Omega\cdot\)m, and 1.15 \(\Omega\cdot\)m for each 1 \({}^{\circ}\)C increase. The research results can provide support for temperature correction of calcareous sand resistivity.
2. When the pore solutions were pure water, tap water, 1% NaCl salt solution, 2% NaCl salt solution, 4% NaCl salt solution, and 6% NaCl salt solution, the resistivity of calcareous sand showed a significant downwards trend, and the differences in resistivity values were significant. When the concentration of NaCl was high, the influence of particle size on the resistivity of saturated calcareous sand could be ignored.
3. The resistivities of three size fractions of calcareous sands decreased with increasing saturation, and the relationship between them was a power function. When they were close to full saturation, the rate of resistivity decline gradually decreased. When the calcareous sands were fully saturated, their resistivity reached the minimum.
4. The larger the porosity of calcareous sands was, the lower the resistivity was. The relationship between the resistivity and relative density of calcareous sand was established using a linear function. The research results can provide support for the establishment of the relationship between particle breakage and electrical resistivity of calcareous sand in the future.  
Conceptualization, H.H. and W.H.; data curation, X.D. and T.L.; formal analysis, H.W., Z.L. and L.W.; methodology, H.H. and W.H.; writing--original draft, H.H. and W.H.; writing--review and editing, W.H. All authors have read and agreed to the published version of the manuscript.  
This research was funded by two grants from the National Science Foundation of China (51978317 and 51979128).  
Not applicable.  
The data used to support the findings of the study are available from the corresponding author upon request.  
The authors appreciate the comments and suggestions provided by the editors and anonymous reviewers.  
The authors declare no conflict of interest.
## 4 Applications of Intelligent Acoustic Monitoring
### Public Safety and Security
#### 4.1.1 Shot Detection and Weapon Classification  
In [96; 97], [PERSON] et al. presented a method and system for acoustic detection of gunshots, which could detect, localise, and classify acoustic events. The system was tested in open and closed shooting ranges, using various firearms and subsonic and supersonic ammunition. The system employed continuous wavelet [103] and Mel Frequency Transformation [104] methods for signal processing, along with a two-layer fully connected neural network for classification. The results showed that the acoustic detector could be reliable for gunshot detection, localisation, and classification.  
In [98], [PERSON] et al. found out that gunshot sounds were common in crimes, causing fear and panic among victims. Additionally, these sounds were associated with high mortality rates. Based on this, the authors focused on efficient gunshot detection as crucial for preventing crimes. They proposed a novel Discrete Wavelet Transform Random Forest Probabilistic (DWT-RFP) feature engineering approach and a meta-learning-based Meta-RF-KN (MRK) method. Experiments on a gunshot sound dataset using 851 audio clips from YouTube showed the MRK approach achieved 99% k-fold accuracy, outperforming state-of-the-art methods. This approach could potentially help prevent crimes.  
In [99], [PERSON] et al. used YAMNet, a deep learning-based classification model, to identify firearm types based on the sounds of gunfire. The technique extracted features from audio data using Mel spectrograms [105]. The study used 1174 audio samples from 12 distinct weapons, achieving an accuracy of 94.96%. The research highlighted the effectiveness of YAMNet in real-world weapon detection and its relevance in forensic, military, and defence applications. The model outperformed existing deep learning and hybrid techniques, and the study emphasised the importance of integrating extra Keras layers for improved training efficacy.
## 2 Channel Modeling of Dual-Polarization for MIMO-TITO Systems
\]  
The channel response matrix, \(H_{TR}\), now represents the DP channel-matrix combining spatial-separation, dual-polarized arrays, global XPD, and finite XPI under Quasistatic Flat-Rayleigh-Fading assumption. Defining  
\[ \begin{cases}A=\cos(\theta)\sin(\phi)\\ B=\cos(\theta)\cos(\phi)\\ C=\sin(\theta)\cos(\phi)\\ D=\sin(\theta)\sin(\phi),\end{cases}  \tag{6}\]  
\(H_{TR}\) now define as:  
\[H_{TR}=\left(\sqrt{\frac{1}{1+k}}\begin{bmatrix}h_{xx}\big{(}B+\delta_{x,y}A \big{)}+h_{yy}\big{(}D+\delta_{y,x}C\big{)}&h_{xx}\big{(}A+\delta_{x,y}B \big{)}+  
As we mentioned and will demonstrate in the following sections, the polarization state in the channel can be influenced by tuning the XPI mechanism in the receiver and transmission antennas. This process is significant and necessary because the interference's effects, and physical phenomena, such as rain, constantly change the channel's conditions and affect the system's performance. In this situation, optimizing the system performance by tuning the XPI and combining advanced MIMO techniques is critical.
# The Resilience of Vegetation to the 2009/2010 Extreme Drought in Southwest China
## 4 Discussion
### Factors Affecting Vegetation Resistance, Recovery, and Resilience  
Vegetation resistance, recovery, and resilience indices are related to many factors, such as water availability [47], temperature [38], altitude [48], biodiversity [49; 50], tree age [51], and tree density [52]. Water scarcity and warming are important factors affecting vegetation growth [48; 53]. In our study, the normalized regression coefficients of surface soil moisture and the resistance of vegetation, NDVI and LAI, in evergreen broadleaf forest, evergreen needleleaf forest, evergreen broadleaf shrubland, deciduous broadleaf shrubland, and grassland were positive and significant, that is, the increase in surface soil moisture could significantly improve the resistance of vegetation (Figure S6). Previous studies also showed that the ability of vegetation to resist drought was closely linked to the moisture availability under conditions of water stress [51; 52]. A sharp decline in soil water impeded vegetation growth, reducing their ability to withstand the extreme drought [54; 55]. When extreme drought continues, vegetation growth and productivity are further reduced [56].
# Optimization Algorithms for Scalable Stream Batch Clustering with k Estimation
## 5 Experiments
### Processing Time Analysis  
Table 5 presents the processing time comparison (in minutes) among all algorithms. For simplicity, the total execution time of the compared algorithms was considered instead of the time for processing individual micro-batches. Total 1 sums the running time for the data sets processed by SPGMS (100K5-2, 1M5-2, 1M10-5, 10M10-5, and KC99), and Total 2 does the same for all data sets. Every cell represents the average and standard deviation of 20 repetitions, including the totals. The values in bold highlight the fastest algorithm and the ones with no significant difference from the fastest for each data set, according to the Friedman test with 95% confidence. SESC was the fastest for all the data sets. ISESC-CD was faster than ISESC (5.2 times on average, according to Total 2), due to its change-detection component being designed to avoid unnecessary full-clustering processing. This  
component was able to avoid full-clustering processing 82% of the time. ISESC-CD was also statistically equivalent to the fastest algorithm over most data sets and the totals. However, unlike SESC, it obtained high-quality results (Table 4) for most of the data sets. Because of the expectation-maximization algorithm, SPGMS was the slowest algorithm for most of the data sets, unable to process them all. Designed to overcome this, SPKMS was 2.2 times faster than SPGMS, considering the Total 1 of Table 5. Due to its simplicity, SGMS was the fastest projection-based algorithm, but not so fast as the evolutionary FEAC-based algorithms. SGMS requires many shuffles through the distributed system (as SPGMS and SPKMS). In short, the fastest algorithm was SESC, followed by ISESC-CD, SGMS, ISESC, SPKMS, and SPGMS.
###### Abstract  
In satellite networks, existing congestion resolution methods do not consider the predictability and stability of paths, leading to frequent path switches and high maintenance costs. In this regard, we propose a novel congestion resolution approach, named MOLM, which introduces a continuous neighbor set during path updates. This set includes nodes capable of establishing sustainable connections with the predecessors and successors of congested nodes. Combined with a multi-objective simulated annealing framework, MOLM iteratively derives an optimal selection from this set to replace congested nodes. Additionally, we employ a Fast Reroute mechanism based on backup paths (FRR-BP) to address node failures. The simulation results indicate that the optimal node endows the new path with optimal path stability and path latency.  
satellite internet; routing algorithm; path stability; latency; simulation experiments 2020 rights 10.12.  
the multi-objective simulated annealing algorithm is used to select neighboring satellites that satisfy both strong path stability and low latency to replace congested nodes, thereby improving the overall performance of the satellite internet system.  
The main contributions of the paper are embodied in the following aspects. (1) Based on the predictability of satellite networks, the concept of a continuous neighbor set is proposed, which includes nodes that can maintain continuous connections with the predecessor and successor of congested nodes. (2) The MOLM algorithm is used, which employs the multi-objective simulated annealing (MOSA) framework to iteratively derive an optimal element from the continuous neighbor set to replace congested nodes within a specific path, generating the final solution aimed at alleviating network congestion. (3) A comprehensive comparative experiment is conducted to demonstrate the performance of the MOLM algorithm, including comparative experiments under different networking methods and varying satellite constellation densities. Finally, the reliability of FRR-BP is measured using the time taken to reconstruct backup paths.  
The rest of the paper is organized as follows. In Section 2, we summarize the work related to satellite network congestion resolution strategies. In Section 3, we introduce the architecture of satellite networks. In Section 4, we first introduce the process of using the MOLM algorithm to address network congestion issues. Then, we introduce the Fast Rerouting mechanism based on backup paths (FRR-BP). In Section 5, a comprehensive experiment is conducted to demonstrate the performance of the MOLM algorithm. In Section 6, we give the conclusion.
# Efficient High-Dimensional Quantum Key Distribution with Hybrid Encoding
## 4 Security Analysis
Key generation efficiency of prepare-and-measure \(d\)-QKDs [47; 48; 49; 50; 83] are comparable with that of our protocol. Our protocol is vulnerable to photon loss noise compared with prepare-and-measure \(d\)-QKDs, as it is shown in \[\frac{1}{\sqrt{d}}\sum_{k=0}^{d-1}\left|l_{k}\right\rangle_{A}\otimes\left|p_{ k}\right\rangle_{B}. \tag{7}\]0 Our protocol employs \(d^{2}\) detectors in the measurement setup, while prepare-and-measure \(d\)-QKDs have \(2d\) detectors. Because of this reason, an effect of a dark count of detectors in our protocol is larger than that in prepare-and-measure \(d\)-QKDs. This means that growth in an error rate of our protocol is higher than that of prepare-and-measure \(d\)-QKDs when a single photon is lost. However, as it is shown in the security analysis, our protocol can prevent certain kinds of side channel attacks against detectors, while security of prepare-and-measure \(d\)-QKDs is threatened even by the first proposal of a detector blinding attack. In consideration of this, the gap between the two secret key rates shown in Figure 6 is not significant. Finally, we note that it is possible to employ state-of-the-art techniques in our protocol, since our protocol is constructed with general experimental elements. For example, in \(d\)-QKD using partial MUBs of OAM [49], they proposed using special single photon OAM modes in their protocol for noise robustness. It is expected that the setups used in the protocol are exploited in our protocol for the same purpose as well.
# Transparent Redirections in Content Delivery Networks
## 5 Evaluation  
The evaluation of the performance was done on two setups. The proposed transparent redirection was compared to the application layer redirection using 302-redirection. In both cases, the request router redirected the requests to the closest surrogate server based on the client's location.  
The solution was evaluated in two different scenarios. The first scenario focuses on the overall delay and performance of the proposed solution. The second scenario presents the solution as a load balancer and compares the performance to an application-layer proxy.