esa-sceva/satcom-chunk-collection huggingface dataset:
# Improving Performance of Cluster Heads Selection in DEC Protocol Using K-Means Algorithm for WSN
## 5 Simulation and Evaluation of DEC and DEC-KM Protocols
### Simulation and Evaluation of DEC-KM
#### 5.2.1 Algorithm Implementation  
The protocol has been implemented in three main stages:  
STAGE 1: Using the parameters from Table 1, implement the network and calculate the initial cluster areas and cluster heads using the DEC protocol.  
STAGE 2: Apply the K-means algorithm for the data calculated in STAGE 1 and make a new clustering.  
STAGE 3: Perform CH Selection, checking if the CH energy is over the threshold; choose the nodes of high energy level close to the centre point in a cluster area and the base station.  
Figure 4: Results of the implementation of standard DEC protocol using MATLAB: cluster heads are marked as bold black circles, and other nodes are marked as colour rhombus; nodes in the same cluster area are marked with the same colour.
## 4 Test Program
### Repeatability of the Tests  
Due to the variability in properties of the materials (mainly geotextiles) and the nature of the \(GR\) test, a 10% uncertainty range in \(GR\) values is expected in carefully conducted tests [30]. To check the repeatability of the experiment, duplicate \(GR\) tests were conducted using GT1 (thin GT) and GT4 (thick GT). Table 6 shows typical test results, demonstrating that the test results are generally repeatable and in good agreement. Moreover, the variation within the \(GR\) values is within 10%.  
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multirow{3}{*}{**Soil**} & \multirow{3}{*}{**Geotextile**} & \multicolumn{6}{c}{**Coefficient of Permeability**} & \multirow{3}{*}{\(GR\)} & \multirow{3}{*}{\(\mathbf{Mass}\) of Particles Retained**} \\ \cline{3-3} \cline{5-10}  & & & & (10\({}^{-9}\) m/s) & & & & & **Mass of Particles Retained** \\ \cline{3-10}  & & \(k_{s}\) & \(k_{sg}\) & \(k_{s}\) & \(k_{sg}\) & \multirow{2}{*}{**0 kPa**} & \multirow{2}{*}{**5 kPa**} & \multirow{2}{*}{**Inside Geotextile (g/m\({}^{2}\))**} \\ \cline{3-3} \cline{5-10}  & & 0 kPa & 0 kPa & 5 kPa & 5 kPa & & & **0 kPa** & **5 kPa** \\ \hline \multirow{3}{*}{C} & **GT1** & **3.44** & **3.17** & 2.69 & 2.45 & 1.08 & 1.10 & 9.6 & 127 & 318 \\  & \(\mathrm{GT1}\)* & 3.46 & 3.19 & 2.68 & 2.44 & 1.10 & 1.07 & 9.6 & 140 & 332 \\  & \(\mathrm{GT4}\)* & 2.0 & 2.44 & 1.99 & 1.81 & 0.82 & 1.10 & 3.73 & 605 & 690 \\ \cline{1-1} \cline{2-10}  & \(\mathrm{GT4}\)* & 2.2 & 2.45 & 2.0 & 1.83 & 0.89 & 1.09 & 3.73 & 623 & 700 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Gradient ratio filtration test results of sility clay (\(i\) = 1.0).  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{3}{*}{**Normal Stress (kPa)**} & \multicolumn{6}{c}{**Fine Particles Retained in Geotextile Fibers (g/m\({}^{2}\)) (\(i\) = 1.0)**} \\ \cline{2-9}  & \multicolumn{2}{c}{**GT1**} & \multicolumn{2}{c}{**GT2**} & \multicolumn{2}{c}{**GT3**} & \multicolumn{2}{c}{**GT4**} \\ \cline{2-9}  & **C** & **M** & **C** & **M** & **C** & **M** & **C** & **M** \\ \hline
0 & 127 & 459 & 271 & 465 & 437 & 503 & 605 & 610 \\
5 & 318 & 506 & 415 & 510 & 555 & 578 & 690 & 701 \\
10 & 306 & 543 & 425 & 544 & 532 & 666 & 704 & 768 \\
15 & 471 & 627 & 441 & 662 & 558 & 726 & 724 & 916 \\
25 & 586 & 708 & 531 & 715 & 698 & 839 & 846 & 939 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Mass of fine particles retained inside the geotextile fibers after the entire filtration test at 48 h.
## 2 Related Works
On the other hand, the mobility-adaptive beacon broadcast (MAB\({}^{2}\)) scheme guarantees a successful tracking of the sending vehicle to a subset of its neighbor vehicles, which successfully receive at least one beacon out of the most recent \(K\) beacons, which is called the guaranteed tracking of degree \(K\)[17]. Despite its theoretically proven optimality in channel bandwidth usage, timely dissemination of beacons, and low tracking failure probability, the MAB\({}^{2}\) scheme encounters challenges in refreshing kinematic information and managing TP, indicating a potential area for further improvement. To the best of our knowledge, this work is the first research to comprehensively address all of the awareness requirements of the beaconing problem in V2X communications, including vehicle detection, tracking, and the mAFD. To address this problem, we adopt the DRL approach because it allows for real-time learning and optimization of policies in complex, dynamic environments, crucial for ensuring the safety and efficiency of V2X communications. Although there are a few DRL approaches in [13; 18; 19; 20], they typically focus on the control of channel congestion by controlling data rate [18; 19; 20], BR [13], or TP [13; 18]. In contrast, our DRL-JCBRTP simultaneously addresses vehicle detection, tracking, and maintaining the mAFD, providing a more holistic solution to the beaconing problem in V2X communications.
# Ensemble Clustering in GPS Velocities: A Case Study of Turkey
## 3 Results and Discussion
### Identification of Blocks  
Continental lithosphere deformation especially in tectonic regions such as Turkey can be provided by GPS data [10]. Elastic blocks that are bounded by active faults can describe velocities derived from GPS data. In geographic space, remaining cluster boundaries with increasing cluster numbers are identified as block boundaries, especially if the boundary of the cluster coincides with an active fault [13]. Ref. [7] gave the results from \(k=2\) to 10 and North and East Anatolian transform faults can be seen as the border of clusters because these two are the most prominent faults. Because Anatolia is divided into more clusters with the increasing number, one can note that there is not a block boundary inside this block. Here, we tried to assess the velocity field for \(k=5\), because over five is not tectonically significant. With five clusters in this region, also Aegean part identifies a cluster and it is compatible with [5]. On the other hand, the eastern part differs from [5] block boundaries because clustering methods determine clusters according to velocity discontinuities. The velocity gradient in the eastern part differs from the fault traces, consequently, cluster borders are not incompatible with [5] in this region.
## 2 Materials and Methods
### Experimental Design  
A three-dimensional motion analysis system (Vicon MX, Vicon Motion Systems, Oxford, UK), sampling at 240 Hz, was used to record lower extremity kinematic data during testing. Kinematic and kinetic data were computed with low-pass filtering at 16 Hz using a fourth-order zero-lag Butterworth filter. Two AMTI force plates with amplifier (Mini-Amp MSA-6, Watertown, MA, USA), sampling at 1200 Hz, were used to record the vertical ground reaction force (vGRF) during testing. Thirty-five reflective anatomical and technical markers were positioned in various places on the body, based on Vicon's Plug-in-Gait full body marker set, and used to derive the bilateral lower limbs and trunk model during testing [32].  
The participants wore close-fitting dark shorts to aid data collection. They performed drop vertical jumps (DVJs) from a box measuring 40 cm in height (Figure 1). Before testing, the trial sequence was demonstrated by research assistants and all participants were allowed to perform several practice jumps to become familiar with the trial procedure. DVJ trials were repeated and recorded until data were obtained from five successful trials. Trials were excluded if the subject lost their balance during the landing stages. All variables were calculated as the mean value of the three trials from the five trials. The first and fifth of the five trials were excluded to eliminate larger variations due to lack of experience and fatigue, respectively.  
A drop vertical jump consisted of two stages: first, landing after dropping down on two force plates from a 40 cm box; and second landing after a maximal vertical jump rebounding from first drop.
## 4 Salinity Origin and Its Impacts on Plants
### Primary Metabolism
#### 4.2.3 Senescence  
Under long-period exposition to salinity, plants undergo ionic stress, which may contribute to premature senescence of mature foliage and hence a decrease of the required photosynthetic zone to maintain biomass accumulation and growth [79; 80]. Salt-stimulated senescence is claimed to be due to ionic pressure of high Na\({}^{+}\) quantities and nutritional deficiencies like a decreased cytoplasmic K\({}^{+}\): Na\({}^{+}\) proportion [81; 82] causing chlorosis and necrosis in mature leaves by destruction of protein production and disruption of enzyme function [83]. In rice leaves, salinity affects several senescence-related variables including membrane permeability, fluorescence of chlorophyll a, and leaf concentration of chlorophyll and protein. The anticipation of increased activity of senescence characteristic enzymes such as isocitrate lyase (ICL) can be observed under saline conditions [84; 85]. The involvement of ICL, a central enzyme of the glyoxylate cycle [86], in the crossroads between salinity and senescence was demonstrated in an experiment showing that the AtICL knockout tomato (Aticl mutant without ICL activity) was much less tolerant to salinity than the isogenic wild type [85].
# Walking-Age Estimator Based on Gait Parameters Using Kernel Regression
## 2 Methods  
### Gait Data  
We utilized a gait database [44] that contains time-series three-dimensional coordinates of skeletal landmarks, recorded by a motion-capture system during straight-line walking under normal gait conditions. This database provides ten non-successive gait cycles for individual participants. Participants walked on a straight 10 m path barefoot at a comfortable speed. We used five gait cycles starting with left-heel contact for 30 women aged over 60 years, 30 women aged 20-30 years, and 15 women aged 35-50 years. In total, we used 375 samples collected from 75 healthy women. Note that the database does not include an equal number of participants for each age category. Furthermore, it comprises a larger number of female participants; hence, we only adopted the data of women. Gait parameters may have a different association with age between men and women [45].  
We conducted a multiple linear regression analysis to establish a baseline performance. According to a power analysis using G*Power [46], the required sample size for testing individual regression coefficients in a two-tailed \(t\)-test, with \(\alpha=0.05\), \(1-\beta=0.80\), and a  
Figure 1: Study scheme. We estimated age based on the height, weight, and gait parameters of walkers using kernel regression analysis. Adapted from [33].  
medium effect size (\(f^{2}=0.15\)), is 55. The number of samples in our dataset exceeds this requirement.
# A Class of Perfectly Secret Autonomous Low-Bit-Rate Voice Communication Systems
## 7 Experimental Evaluation
### Potential Attacks and Countermeasures  
Despite its strong theoretical foundation, the APS-VCS system must be resilient to various potential attacks. Below, we discuss major threats and how the proposed approach successfully mitigates them.  
_Man-in-the-Middle (MitM) Attacks_: Since the SKD protocol relies on a public authenticated channel, an adversary could attempt to inject or manipulate messages. The use of authentication mechanisms and error correction ensures that only legitimate parties can participate in key generation, effectively preventing MitM attacks.  
_Eavesdropping Attacks_: The Vernam cipher ensures perfect secrecy, making intercepted ciphertexts indecipherable without the secret key. Additionally, since secret keys are distilled in real time and never reused, an eavesdropper gains no useful information even if past communications are compromised.  
_Side-Channel Attacks_: Attackers may attempt to extract key information by analyzing power consumption, timing variations, or electromagnetic emissions. Implementing countermeasures such as randomized computational delays and hardware shielding can mitigate these risks.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Criterion** & **LSP-Based Synthesizer** & **QKD Systems** \\ \hline Deployment Feasibility & High—Works with existing digital networks & Low—Requires dedicated infrastructure \\ \hline Autonomy & Fully autonomous, no external TTP needed & \
\begin{tabular}{c} Requires trusted quantum network \\ infrastructure \\ \end{tabular} \\ \hline Scalability & Easily deployable over VoIP, LTE, radio & Limited to fiber-optic or satellite links \\ \hline Synchronization with Speech & Designed to match real-time low-bit-rate & \\ Encryption & voice coders & Often too slow for real-time voice encryption \\ \hline Security Model & Information-theoretic security with OTP &
\begin{tabular}{c} Provable key distribution security but \\ requires classical encryption \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table}
Table 9: LSP-based speech synthesis vs. QKD for real-time secure speech.  
_Replay Attacks_: To prevent adversaries from capturing and replaying key exchange messages, each SKD session includes time-varying elements and freshness indicators. This ensures that old messages cannot be reused to compromise the system.  
_Quantum Attacks_: While current quantum computers do not threaten the information-theoretic security of the Vernam cipher, they could weaken authentication and key distillation mechanisms. Future enhancements could incorporate quantum-resistant authentication schemes to ensure long-term security.
# Research on Semi-Active Vibration Control of Pipeline Based on Magneto-Rheological Damper
## 4 Experimental Study on Semi-Active Vibration Control
### Two-State Vibration Control Experiment  
Two-state control is the simplest control method, and it is also the most widely used semi-active control strategy for MR damper. The two-state control process is shown in Figure 13. The strategy of two-state control is to set the amplitude reference on both sides of the structural vibration equilibrium position. When the structural vibration amplitude is less than the set value, the control current is not applied to the MR damper, and the MR damper only passively outputs the foundation viscous damping force to attenuate the pipeline vibration. When the structural vibration amplitude is greater than the set reference value, a control current is applied to the MR damper, and the MR damper is controlled to output a damping force, which can control the structural vibration amplitude within a certain range. When the sinusoidal excitation frequencies are 1 Hz, 5 Hz, and 10 Hz, the vibration response test results of the pipeline under the two-state vibration control are shown in Figure 14.  
When the vibration control of the pipeline is controlled by the two-state vibration control, the statistical results of the vibration response of the pipeline under different excitation frequencies are shown in Table 2.  
As shown in Table 2, when the vibration of the pipeline is controlled by the two-state control, the displacement and acceleration of the pipeline are significantly reduced. As shown in Table 2, the displacement drop of the pipeline vibration at different excitation frequencies ranges from 14.5904 to 21.9312 dB, the acceleration drop range is from 4.4697 to 14.5449 dB, the displacement attenuation  
Figure 14: Pipeline vibration response under two-state control and excitation frequency of 1, 5, 10 Hz: (**a**) Displacement-time curve (1 Hz); (**b**) Acceleration-time curve (1 Hz); (**c**) Displacement-time curve (5 Hz); (**d**) Acceleration-time curve (5 Hz); (**e**) Displacement-time curve (10 Hz); (**f**) Acceleration-time curve (10 Hz).  
range is from 81.36% to 91.99%, and the acceleration attenuation range is from 40.23% to 81.26%, and the vibration isolation rate ranges from 88.86% to 98.28%.
## 2 Materials and Methods
### Solutions Preparation  
All Ni\({}^{2+}\) solutions were prepared with Ni(NO\({}_{3}\))\({}_{2}\) using ultrapure water or soil colloid suspensions to adjust the concentrations of Ni\({}^{2+}\) from 0 to 2 mg\(\cdot\)L\({}^{-1}\). The initial pH was adjusted to be 5.5, 6.5, or 7.5, as required, using 0.1 mol\(\cdot\)L\({}^{-1}\) HNO\({}_{3}\) or 0.1 mol\(\cdot\)L\({}^{-1}\) NaOH. The ionic strength (IS) was adjusted to 0 mmol\(\cdot\)L\({}^{-1}\), 3 mmol\(\cdot\)L\({}^{-1}\), and 30 mmol\(\cdot\)L\({}^{-1}\) by NaNO\({}_{3}\). Humic acid (HA) at a concentration of 20 mg\(\cdot\)L\({}^{-1}\) was selected to represent the organic matter.
# Study on Low Temperature Drying Characteristics of Chicken Manure in a Humid Environment
## 3 Results and Discussion
### Drying Characteristics at Different Depths of Manure Layer  
Analyses of drying curves (Figure 5) revealed that the depth of the manure layer had a major impact on the low-temperature drying process in a humid environment. Obviously, with increasing manure depth, the drying time increased. The time required to dry the 60 mm manure layer was more than that for 40 mm and 20 mm by about 16.7% and 55.6%, respectively. This was because the manure layer depth will affect the migration and diffusion distance of water inside the chicken manure to the surface of the manure and the free water to the top of the manure layer. The thicker the manure layer, the longer the migration time of water inside the chicken manure to the surface of the manure and the free water to the top of the manure layer. At the same time, the thickness of the manure layer also affects the ventilation resistance. The thicker the manure layer, the greater the ventilation resistance and the smaller the effective air volume through the fecal layer. We can also see from Figure 5a, the distance between drying curves decreased with an increase in the manure depth, and the drying curves for 40 mm and 60 mm manure depths followed each other very closely. It indicates that the capacity of wet air to carry away moisture was beginning to reach its limit with the increase in manure layer thickness.  
Comparing the drying rate curves in Figure 5b, the trend of cure was found to be similar to those in Figures 3b and 4b. The drying process had only a falling rate period, with no accelerated or constant rate period, and there was a turning point in the falling rate period. Furthermore, the turning point of the drying rate curves appeared earlier with the decrease in manure depth. The 20 mm manure depth had the highest drying rate in the early period of the drying process, but the drying rate of the 60 mm manure depth was superior in the later period. The results were the same as the conclusions drawn by [PERSON] [8]. This was because the thinner the manure layer, the sooner the free water was removed, and it was mainly the capillary water, adsorption water, and bound water that remained in the chicken manure in the later period.  
The above results also indicated that the drying time of the low-temperature drying process in a humid environment was more than 24 h, which would increase the disposal cycle of the chicken manure. Therefore, it was necessary to increase the drying temperature and air velocity or reduce the thickness of the manure layer to shorten the drying time to within 24 h. In actual production, the drying temperature could be increased by using an auxiliary heat source to accelerate the drying rate and shorten the drying time. Air velocity and manure thickness could be adjusted artificially.  
Figure 5: (**a**) Drying curves of chicken manure at different manure depths; (**b**) drying rate curves of chicken manure at different manure depths. Note: The dotted line in the figure indicates that the wet basis moisture content is 30%.
# GNSS Multipath Detection Using Continuous Time-Series C/N0
## 1 Introduction
In terms of GNSS receiver correlator-based techniques, several popular methods are available, such as the narrow correlator, strobe correlator, and multipath parameter estimation [13; 14; 15]. These techniques are effective in reducing multipath errors provided an LOS signal is received. In the case of receiving an NLOS signal, the correlator occasionally tracks an NLOS signal because the amplitude of an NLOS signal is higher than the amplitude of an attenuated LOS signal. Our new approach for detecting an NLOS signal is simply based on the continuous time-series C/N\({}_{0}\) for a certain period. If the local minimum of the satellite C/N\({}_{0}\) is less than the determined threshold, the satellite is not used for positioning for a certain period, even if the C/N\({}_{0}\) is recovered over the threshold. The threshold is determined using the average C/N\({}_{0}\) values according to the elevation angle. The threshold is actually set at \(-10\) dB-Hz from the above-average values in each satellite system. Once the satellite C/N\({}_{0}\) decreases to less than the determined threshold, these signals are considered to be inappropriate for positioning for a certain period because an LOS signal without strong reflection never decreases below the threshold. The details for determining the period in which the satellite is not used for positioning are introduced later. The study consisted of the following, as outlined in the remainder of the paper: first, the C/N\({}_{0}\) values of all GNSS satellites obtained for 30 min in a typical environment that was likely to receive NLOS signals were thoroughly investigated. Simultaneously, the postprocessed pseudo-range residuals for all GNSS satellites were estimated by providing the precise antenna position, and these were compared to identify the features of satellites contaminated by NLOS signals. In this case, the NLOS signal included both a reflected wave and diffracted wave. To estimate the residuals, one QZSS was selected to estimate the receiver clock error correctly because the highest satellite was QZSS 195, and its multipath error was very small, even in dense urban areas. Thereafter, GNSS with a large pseudo-range residual over 15 m was selected to verify the C/N\({}_{0}\) fluctuations. Based on these data, our new approach for detecting NLOS signals was introduced. We also confirmed the validity of using both the threshold and period of exclusion from positioning for this approach. Subsequently, three test configurations were established, and the performances of the differential GNSS (DGNSS) and RTK-GNSS were evaluated while using the proposed method. In all three tests, the DGNSS positioning accuracy was improved dramatically using the selected satellites based on the new concept. Moreover, numerous correct fixed solutionsof the RTK-GNSS were validated. In fact, few correct fixed solutions were obtained without the new satellite selection method.