esa-sceva/satcom-chunk-collection huggingface dataset:
## Appendix B Influence of Division into Bins on the Values of the Obtained Statistical Tests  
The values of the obtained statistical tests depend on the method of dividing the range of the analyzed angles into bins. In the works dealing with the study of the orientation of galaxies in clusters [9; 48; 49], approaches were used to perform analyses using a different number of intervals, and comparing the obtained differences. This is the recommended way of proceeding, among others, in cases where the number of analyzed galaxies is small and does not satisfy theoretical test conditions, as well as in the case of tests that are particularly sensitive to the binning procedure, such as the Kolmogorov tests.  
Alternatively, for some statistical tests, it is also possible to repeat the analysis without dividing the angle ranges into bins. The Kolmogorov-Smirnov test, Cramer von-Mises test and [PERSON] test, calculated in this way, are presented in Tables A1-A4. These tables also contain the results of these tests calculated using divisions into 18 bins. Analysis of the Kolmogorov--Smirnov and Cramer von-Mises tests showed that, in the case of our research, with calculations using both methods, the obtained statistical values do not differ significantly. An analogous situation also takes place in the case of variable \(\bar{F}\) in Formula (25), but for the range of the angle divided into bins, the values of the variable are \"shifted\" in the direction of \"larger values\". This tendency is reflected in the values of the \(U^{2}\) statistic. Here, however, the deviations are larger and in both directions, which means that in a certain number of cases, we get negative values in terms of the \(U^{2}\) statistic. CDF values for Kolmogorov, Cramer-von Mises and Watson tests are presented in Figure A1. This proves that, at least for the Watson test, the binning process is important. As a result, if we compare the statistics obtained for the actual distributions of the orientation angles of the galaxies with the theoretical distributions of galaxies, we must remember that the binning process is the same in both cases (and this is what we do in present paper).  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Group**} & \multicolumn{3}{c}{**Angle Range Not Divided into Bins**} & \multicolumn{3}{c}{**Angle Range Divided into 18 Bins**} \\  & \(\mathbf{\lambda}\) & \(\mathbf{W^{2}}\) & \(\mathbf{\bar{F}}\) & \(\mathbf{U^{2}}\) & \(\mathbf{\lambda}\) & \(\mathbf{W^{2}}\) & \(\mathbf{\bar{F}}\) & \(\mathbf{U^{2}}\) \\ \hline  
(-0.1816\) \\ \hline \hline \end{tabular}
\end{table}
Table 10: Comparison of statistical tests calculated by dividing and not dividing the range of the analyzed angle \(\eta\) into bins, with the inclination taken directly from the NBG Catalog.  
Figure 17: The Cumulative Distribution Function (CDF) of the angle \(\delta_{D}\) (left panel) and \(\eta\) (right panel) for analyzed statistics for group 12. Comparison of statistical tests calculated by dividing and not dividing the range of the analyzed angles into bins From up to down, we present statistics: \(\lambda\), \(W^{2}\) and \(U^{2}\).
# Low-Thrust Nonlinear Orbit Control for Very Low Lunar Orbits
## 6 Concluding Remarks  
This research addresses the application of a Lyapunov feedback controller to inject a spacecraft into a very low lunar orbit, with subsequent maintenance maneuvers. The space vehicle is assumed to be equipped with a steerable and throttleable low-thrust engine. The formulation of the nonlinear constraints is simplified with respect to previous works by employing modified equinoctial elements. The stability analysis is developed in a general framework that includes time-varying orbit elements and proves that the asymptotic stability is quasi-global. Monte Carlo campaigns are carried out for two target orbits with different inclination and two operational scenario, i.e., a circular target orbit or an elliptic target orbit with assigned minimum radius at periselenium and maximum radius at aposelenium. The numerical simulations demonstrate the capability of the strategy at hand to perform orbit acquisition and maintenance despite third body and gravitational perturbations. Very-low-altitude lunar orbits with tight control of the orbit elements appear very attractive for the deployment of satellite constellations. Even though this research investigates operational scenarios with the only precession of the right ascension, the proposed feedback control law can be applied to target non-Keplerian trajectories with time-varying orbital elements.  
Conceptualization, M.P.; methodology, M.P. and E.M.L.; validation, M.P., S.C. and P.T.; formal analysis, M.P. and E.M.L.; investigation, E.M.L.; resources, M.P., E.M.L., S.C. and P.T.; data curation, E.M.L.; writing--original draft preparation, E.M.L.; writing--review and editing, M.P., S.C. and P.T.; supervision, M.P., S.C. and P.T.; project administration, M.P., E.M.L., S.C. and P.T.; funding acquisition, not applicable. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The paper contains all the data needed for reproducing the numerical results.  
The authors declare no conflicts of interest.  
The following abbreviations are used in this manuscript:  
\begin{tabular}{l l} RAAN & Right Ascension of the Ascending Node \\ MCI & Moon Centered Inertial \\ LVLH & Local Vertical Local Horizontal \\ LH & Local Horizontal \\ \end{tabular}
###### Abstract
The above-mentioned traditional identification and access control protocols are mainly based on cryptographic mechanisms, most of which run above the data link layer. Once the key is leaked, the network security cannot be guaranteed. Further, the third-party server authentication-based identification methods need to consume additional resources and increase the power consumption and complexity of the system [12], which makes it difficult to achieve non-perceptual authentication. In recent years, wireless communication network security has begun to rely on the physical layer security technology, and the use of non-cryptographic identification mechanisms can achieve better performance against identity attacks compared to traditional authentication methods [13], which may be the future development trend of user identification technology of V2X systems [14]. In the field of physical layer security, radio frequency fingerprint (RFF)-based identification technology is one of the current researching hot directions, which identifies and authenticates each wireless device individual by extracting the hardware characteristics that are unique and difficult to clone. Therefore, in this paper an RFF-based V2X identification and authentication mechanism is explored and put forward for the DSRC technology based on the IEEE 802.11p protocol, which can also achieve better recognition results in the scene of moving vehicles. The flow chart of RFF extraction and identification process for DSRC intelligent vehicle networking is shown in Figure 1. After the DSRC device to be identified sends out the signal, the signal is collected by the receiver after passing through the mobile channel. When the signal preprocessing is completed, channel characteristics and other environmental interference factors are removed and only the RFF characteristics of the device itself are retained. Subsequently, the feature extraction of RFFs, the design of classifiers, the training and registration of fingerprint database, and the identification and authentication process are carried out in sequence. The structure of this paper is organized as follows. The second section reviews the related studies in the previous literature and lists the contribution of this paper. The third section introduces the IEEE 802.11p protocol standard and describes the signal acquisition and preprocessing process. The fourth section presents the novel radio frequency fingerprint extraction and identification methods valid in complex mobile environment. The fifth section introduces the experiment and analyzes the results. The final section summarizes the research work done in this paper.
## 2 State of the Art
### Classical Approaches  
Early biped walking of robots involved static walking with a very low walking speed [6]. The step time was over 10 seconds per step and the balance control strategy was performed through the use of COG (center of gravity). Here the projected point of COG onto the ground always falls within the supporting polygon that is made by two feet. During the static walking, the robot can stop the walking motion any time without falling down. The disadvantage of static walking is that the motion is too slow and wide for shifting the COG. Below, there are some recent works solving the problem of biped walking based on classical approaches.  
[PERSON], [PERSON], and [PERSON] [11] describe a walking control algorithm for biped humanoid robots that considers an uneven and inclined floor. Some online controllers worked well for a slightly uneven and inclined floor, but the robot immediately fell down when the floor inclinations exceeded a certain threshold. Hence, six online controllers (upright pose controller, landing angular momentum controller, landing shock absorber, landing timing controller, landing position controller, and vibration reduction controller) were developed, designed through simple mathematical models and experiments, and then suitable activation periods were planned in a walking cycle. Each online controller has a clear objective and the controllers are decoupled from each other. To validate the performance of the online controllers, walking experiments on an uneven and inclined aluminum plate were performed.  
The authors in [12] describe a proposed method for planning walking patterns, which includes the ground conditions, dynamic stability constraint, and relationship between walking patterns and actuator specifications. They generate hip and foot trajectories, and based on the computation of the zero moment point, they select the most stable trajectory. As a result of this approach, the system can adjust to the ground condition by adjusting the values of foot parameters. The system was validated using a dynamic simulator and a real robot. Recently, deviation control was implemented in the planning stage with a trajectory correction during the gait cycle [13].  
In [2], an online gait trajectory generation method is proposed. The gait trajectory has continuity, and smoothness in variable period and stride to realize the various bipedal walking gaits. The method is tested using simulation and experiment. Recently, control techniques have been applied to balance a biped robot while walking in slopes [14], along with the use of central pattern generation [15; 16].
###### Abstract  
The network area is extended from ground to air. In order to efficiently manage various kinds of nodes, new network paradigms are needed such as cell-free massive multiple-input multiple-output (CF-mMIMO). Additionally, security is also considered as one of the important quality-of-services (QoS) parameters in future networks. Thus, in this paper, we propose a novel deep learning-based secure multicast routing protocol (DLSMR) in flying ad hoc networks (FANETs) with cell-free massive MIMO (CF-mMIMO). We consider the problem of wormhole attacks in the multicast routing process. To tackle this problem, we propose the DLSMR protocol, which utilizes a deep learning (DL) approach to predict the secure and unsecured route based on node ID, distance, destination sequence, hop count, and energy to avoid wormhole attacks. This work also addresses key concerns in FANETs such as security, scalability, and stability. The main contributions of this paper are as follows: (1) We propose a deep learning-based secure multicast routing protocol (DLSMR) to establish a high-stability multicast tree and improve security performance against wormhole attacks. In more detail, the DLSMR protocol predicts whether the route is secure based on network information such as node ID, distance, destination sequence, hop count, and remaining energy or not. (2) To improve the node connectivity and manage multicast members, we propose a top-down particle swarm optimization-based clustering (TD-PSO) protocol to maximize the cost function considering node degree, cosine similarity, cosine distance, and cluster head energy to guarantee convergence to the global optima. Thus, the TD-PSO protocol provides more strong connectivity. (3) Performance evaluations verify the proposed routing protocol establishes a secure route by avoiding wormhole attacks as well as by providing strong connectivity. The TD-PSO clustering supports connectivity to enhance network performance. In addition, we exploit the impact of the mobility model on the network metrics such as packet delivery ratio, routing delay, control overhead, packet loss ratio, and number of packet losses.  
CF-mMIMO; clustering; deep learning; flying ad hoc networks; secure multicast routing; security; wormhole attack +
Footnote †: 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/))).
# Massive MIMO Indoor Transmissions at 38 and 65 GHz Applying Novel HBF Techniques for 5G
## 3 Methodology
### Implemented Algorithms  
Two massive MIMO-OFDM algorithms have been simulated to study their application in indoor environments for 5G millimeter communications.  
Firstly, due to its low complexity and high speed, the HBF algorithm for orthogonal frequency division multiplexing (OFDM)-based systems described in [11] was selected. Secondly, the SFBC technique [23; 24] has been also added to the previous algorithm (SFBC-HBF) to experimentally investigate the benefit of applying these techniques when the SNR is low.
# An Efficient BDS-3 Long-Range Undifferenced Network RTK Positioning Algorithm
###### Abstract
The proposed method makes full use of the advantages of the BDS-3 full constellation to provide multi-frequency observation data. First, the phase integer ambiguity of a reference station network is calculated using the random walk constraint model of the atmospheric delay error between epochs. Then, the classification undifferenced error correction of the reference station network is realized, and the classification undifferenced error correction of the rover station is obtained via interpolation, using an inverse distance weighting algorithm. The phase integer AR and position parameter calculation of the multi-frequency BDS-3 data is performed. Finally, the BDS-3 long-range URTK positioning algorithm is verified and analyzed experimentally using the measured continuous operation reference station (CORS) network data.
## 3 Results
### Regression Model Parameters and Coefficients  
The dataset consisting of demographic data, standardized functional parameters, and PCs was randomly divided into train and test data in a 70:30 ratio, with no repeating samples. The training dataset was used to train an elastic-net regression model and the model parameters for the train and test datasets are presented in Table 8. There were no large discrepancies between the results of the two datasets regarding RMSE, R2, or the correlation of the predicted values with the actual cognitive score.  
The absolute values of non-zero component coefficients are presented in Figure 1 to showcase the variable importance. The two most prominent variables in the model were years of education and LOS time. Variables with medium importance were the \"yes\" answer regarding regular visual exams, testing time PC, SRS better, and olfactory discrimination score. Stride Length CoV, MS CoV, age, sentence recognition PC, PTA of the better ear, SRS average, PS phase of the gait cycle, stance duration, SRS total number of mistakes, and cadence were included in the model but had minimal contributions to the prediction. When the variables with minimal contribution were omitted from the prediction calculation, the remaining six variables were still able to explain approximately 46% of the K-MoCA variance. Based on the aforementioned six-variable model, the K-MoCA score can be calculated as follows:  
\[\begin{split}\text{KMoCA}_{\text{predicted}}=24.412+0.855\times \text{Years of education}-0.509\times\text{LOStime}+0.342\times\text{Ophthalalmologist(YES)}\\ +0.277\times\text{PS testing time PC}+0.257\times\text{SRS better}+0.185\times\text{Olfactory discrimination}\end{split} \tag{1}\]  
The correlations between the K-MoCA score and the five quantitative variables with substantial contributions to the prediction are presented in Figure 2. The correlation graphs for the variables which showed significant correlations to the cognitive score but were not  
Figure 1: Variable importance of the components included in the regression model. Absolute coefficients higher than 0.5 are presented in green; absolute coefficients between 0.1 and 0.5 are presented in yellow; absolute coefficients lower than 0.1 are presented in red.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Dataset** & **RMSE** & **R2** & **K-MoCA Correlation Coefficient** & **Lambda** & **Alpha** \\ \hline Train & 2.119 & 0.493 & 0.569 & & \\ Test & 2.017 & 0.420 & 0.524 & & \\ \hline \hline \end{tabular} RMSE, root-mean-square error.  
\end{table}
Table 8: Elastic-net regression model.  
included in the model are presented as Supplementary Material in Figures S1-S13. With the exception of LOS time, the remaining variables were positively correlated with the cognitive score. The participants with more years of education, higher sentence recognition and odor discrimination abilities, and better static and dynamic postural stability obtained higher scores on the K-MoCA test.
# Stability of MSW Landfill Slopes Reinforced with Geogrids
## 1 Introduction
In particular, studies on field observations of the results obtained by numerical and theoretical studies are quite limited. Subjects such as the long-term behavior of geogrids, the effect of mechanical creep, and the friction between geogrids and MSWs still need to be investigated. Friction characteristics between synthetic materials and geotechnical materials also have an important impact on slope stability. Interface shear behavior of synthetic and geotechnical materials has been studied recently due to slope failures in landfills. [PERSON] et al. [12] investigated the properties of different interfaces in landfills using laboratory experiments. In the study by [PERSON] and [PERSON] [13], the geotextile/geomembrane interfacial shear behavior was investigated experimentally and generalized interfacial shear mechanisms were proposed based on the results obtained. [PERSON] et al. [14] performed a study on the cyclic interface shear between geomembranes and sandy gravel. At the end of the study, a new empirical correlation was suggested. In the experimental study carried out by [PERSON] et al. [15], shear tests were performed at the geomembrane/geotextile and geomembrane/geocomposite/sand liner interfaces where the normal stress changes at different shear stages. According to the results obtained from the study, it was stated that the effects of normal stress changes on the lining interface strength should be considered in the slope stability analysis of MSW landfills. A study was carried out experimentally investigating the interface creep behavior between geomembranes and geotextiles in the lining system by [PERSON] et al. [16]. Conventional direct shear tests were conducted using different combinations of geomembranes and geotextiles. It was recommended to conduct longer-term geomembrane-geotextile interface creep tests in order to understand the interface creep mechanism in depth. This study presents the slope stability analysis of MSW landfills carried out using finite element and limit equilibrium methods. Finite element analyses were performed using PLAXIS [17], and limit equilibrium analyses were performed using the SLOPE/W [18] computer programs. The stability behavior of the landfill slopes was analyzed for both unreinforced and geogrid-reinforced conditions. A landfill slope model was selected for the analysis, and model parameters were obtained from the studies available in the literature. In this study, the optimum value of the vertical distance between the geogrid reinforcements and the number of reinforcements, which increase the FS of the MSW slope, are obtained, and the necessary recommendations for practical applications are presented.
# Effect of Aggregate Type on the Shear Behavior of Reinforced Lightweight Concrete Beams
## 2 Research Significance  
Despite the extensive body of research on LWAC, the precise effects of different aggregate types and their physical properties on the shear capacity of RC beams remain insufficiently understood. The research begins with a comprehensive literature review to establish a theoretical foundation, followed by the development of ALWAC mix proportions aimed at achieving targeted concrete strength and density. The experimental phase involves conducting standardized tests on a total of 12 RC beams to analyze shear strength and other mechanical properties, with subsequent data analysis evaluating the impact of aggregate types on shear behavior. Predictive models, based on empirical data, aim to improve the accuracy of shear strength predictions, with further validation and optimization of the findings. This study holds significant potential to enhance design accuracy through more precise engineering calculations, develop sustainable and cost-effective construction materials, and influence future regulatory standards.
# Performance Evaluation of a Long-Span Cable-Slayed Bridge Using Non-Destructive Field Loading Tests
## 2 Non-Destructive Field Loading Test for Pingnan Xiangszhou Bridge
### Structural Theoretical Calculation for Pingnan Xiangszhou Bridge  
#### 2.4.1 Geometric and Physical Parameters of Pingnan Xiangszhou Bridge  
The main beam adopts a split double-box composite beam section, in which the bridge deck of the composite beam is composed of C55 concrete (Elasticity modulus: \(E_{c}\) = 3.55 \(\times\) 10\({}^{4}\) MPa, bulk density: \(\gamma\) = 26 kN/m\({}^{3}\)) and the main body of the steel beam is composed of Q345C steel (\(E_{s}\) = 2.06 \(\times\) 10\({}^{5}\) MPa, \(\gamma\) = 78.5 kN/m\({}^{3}\)). The center height of the composite beam is 3.50 m, the top plate is provided with 2% cross slope, the bottom plate is horizontal, and the full width of the main beam is 33.50 m. The stay cable adopts a parallel steel strand cable system. The cable body is composed of multiple unbonded high-strength galvanized steel strands with a tensile strength of 1860 MPa, and the outer layer is equipped with a high-density polyethylene (HDPE) cable sleeve. The cable tower uses a diamond-type cable tower structure and C50 concrete (\(E_{c}\) = 3.45 \(\times\) 10\({}^{4}\) MPa,  
Figure 3: Long cables hinged at both ends.  
\(\gamma\) = 26 kN/m\({}^{3}\)). The total height of the cable tower above the tower base is 147.30 m. C30 concrete (\(E_{c}\) = 3.0 \(\times\) 10\({}^{4}\) MPa, \(\gamma\) = 26 kN/m\({}^{3}\)) is used for the capping beam, transition pier body, auxiliary pier body, and bearing platform.