esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Discussion
### SMAP/CYGNSS TB Uncertainties
#### 4.6.2 CYGNSS Reflectivity Uncertainties  
Uncertainty in CYGNSS observations also introduces uncertainty into SMAP/CYGNSS TBs. CYGNSS data are calibrated to optimize retrievals over the ocean surface, which does not necessarily translate to an optimization of retrievals over land. In addition, there is uncertainty in some of the ancillary variables in the bistatic radar equation. Most prominently, the GPS effective isotropic radiated power (EIRP) for the v2.1 data is estimated from a lookup table and does not consider variations in transmit power over time or space. Some of the assumptions we made also introduce uncertainty into the reflectivity values: (1) the assumption that CYGNSS retrievals over land are based on completely coherent reflections; and (2) the 3 \(\times\) 3 km gridding of CYGNSS reflectivity values, which does not account for the elongated footprint of CYGNSS observations. Future work will include estimating a bulk uncertainty for CYGNSS reflectivity values and propagating that uncertainty to TB and NSSM.
###### Abstract  
Plant primary production is a key factor in ecosystem dynamics. In environments with high climatic variability such as the Mediterranean region, plant primary production shows strong seasonal and inter-annual fluctuations, which both drive and interplay with herbivore grazing. Knowledge on the responses of different vegetation types to the variability in both rainfall and grazing pressure by wild and domestic ungulates is a necessary starting point for the sustainable management of these ecosystems. In this work we combine a 15 year series of remote sensing data on plant production (NDVI) with meteorological (daily precipitation data) and ungulate abundance (annual counts of four species of wild and domestic ungulates: red deer, fallow deer, cattle, and horses) in an iconic protected area (the Dofana National Park, SW Spain) to (i) estimate the impact of intra- and inter-annual variation in rainfall and herbivore pressure on primary production, for each of four main vegetation types; and (ii) evaluate the potential impact of different policy (i.e., herbivore management) strategies under expected climate change scenarios. Our results show that the production of different vegetation types differed strongly in their responses to phenology (a surrogate of the effect of climatology on vegetation development), water availability (rainfall accumulated until the phenological peak), and grazing pressure. Although the density of domestic ungulates shows a linear, negative effect on the primary production of three of the four vegetation types, differences in primary production and phenology among vegetation types increase ecosystem resilience to both climatological variability and grazing pressure. Such resilience may, however, be reduced under the conditions predicted by climate change models, if the moderate predicted reduction in rainfall levels combines with moderate to high densities of domestic ungulates, resulting in important reductions in primary production that may compromise plant regeneration, leading to irreversible degradation. New management strategies taking advantage of habitat heterogeneity and phenological alternation, more flexible stocking rates, and the redistribution of management units should be considered to mitigate these effects. The use of available remote sensing data and techniques in combination with statistical models represents a valuable tool for developing, monitoring, and refining such strategies.  
plant primary production; phenology; habitat heterogeneity; grazing; ungulates; livestock; climate change; remote sensing 2021
## 4 Engineering Example Analysis
### Vibration-Reduction Effect
As is shown in Figure 17, this is due to the positive stiffness effect and large damping effect of the CLNVD under fortification earthquakes and the negative stiffness effect and large damping effect under rare earthquakes. In summary, by utilizing the current optimization method, the CLNVDs can achieve high displacement amplification and energy dissipation capabilities, thereby effectively controlling the structure's seismic response. It should be noted that to guarantee the normal work of the CLNVD, the beams connected to the CLNVD and the columns directly associated with the beams should be reinforced. These reinforcing components are called substructures. This paper uses the internal forces under rare earthquakes to strengthen the substructure design. The research on the amplification efficiency of the CLNVD in this study mainly focuses on the framework structure. For frame shear wall structures and shear wall structures, the inter-story bending deformation accounts for a large proportion of the total inter-story deformation. Therefore, in such structures, the displacement amplification coefficient and energy dissipation coefficient of the CLNVD will deteriorate. This paper only discusses the displacement amplification effect and the energy dissipation of CLNVD and does not discuss the control effect of the CLNVD on the inter-story displacement and floor shear force of the structure under earthquake action. Meanwhile, the out-of-plane deformation of the CLNVD will have adverse effects on the displacement of the viscous damper. The above points are not covered in this paper, and we will further improve our research on the amplification and damping effects of CLNVD in future work. CLNVD is a combination of the intermediate column-lever and negative stiffness damping system, helping to achieve large displacement amplification capacity and energy dissipation capacity. The mentality and conclusions of this study also have certain reference significance for the combination of other types of amplification devices and negative stiffness dampers (such as scissor-style negative stiffness damper, toggle-scissor negative stiffness damper, etc.). The CLNVD possesses good energy dissipation capacity and can be used not only in buildings but also to control the deformation of transmission towers under earthquake or wind loads. Marine drilling platforms can also use the CLNVD to increase their ability to withstand wave loads, wind loads, or earthquakes.
# A 6 DOF Virtual Environment Space Docking Operation with Human Supervision
## 5 Conclusions  
In this paper, we presented a co-simulation framework for a real-world and virtual-world 6 DOF platform to mimic the dynamic variability in a docking mechanism for a space rendezvous. The problem of controlling a challenging LPV system using a single type of controller in all operational zones has been addressed. A new approach has been introduced by using fractional order controllers, and a rationale for a generalized approach for LPV systems has been proposed. The simulation results indicate that the proposed approach works satisfactorily and supports the claim that fractional order control is an appealing solution to complex control problems. Further analysis of the control performance in the presence of unknown varying time delays can be evaluated in terms of tele-operation delays for maintenance, failure emergency cases, etc.  
Conceptualization, C.C. and C.M.I.; methodology, C.M.I., C.I.M. and C.C.; software, C.I.M., C.M.I. and C.C.; validation, M.B., C.M.I., C.I.M. and C.C.; formal analysis, C.M.I.; investigation, C.M.I.; resources, C.C., C.M.I. and M.B.; data curation, C.C. and C.M.I.; writing--original draft preparation, C.M.I. and C.C.; writing--review and editing, M.B., C.M.I., C.I.M. and C.C.; visualization, M.B., C.M.I., C.I.M. and C.C.; supervision, C.M.I.; project administration, C.C. and C.M.I; funding acquisition, C.M.I. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The authors acknowledge [PERSON] and [PERSON] for their work on this setup during their Masters thesis at Ghent University and Ghent University Special Research Fund MIMOPREC 020-018. Part of this work has been done within a Master thesis program at Ghent University in collaboration with QINETIQ nva Antwerp, Belgium, a subcontractor of European Space Agency. The real parameters of the simulator are not disclosed in this paper in accordance with the confidentiality agreement between the parties. [PERSON] was supported by a grant from the Romanian Ministry of Education and Research, CNCS-UEFISCDI, project number PN-III-P1-1.1-TE-2019-0745, within PNCDI III.  
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.  
Figure 9: Step responses for the adaptive controller for three legs for the first case, \(P_{1}(s)\) (**left**), and the second case, \(P_{2}(s)\) (**right**).
# An Image-Processing Method for Extracting Kinematic Characteristics of Droplets during Pulsed GMAW
## 3 Extraction of Droplet Region by Image Processing  
In this part, images with a translucent arc such as that shown in Figure 2b were selected as the study object of the image processing. Certainly, the interference of the arc in images undoubtedly increases the difficulty of image processing. In order to solve this problem successfully, a droplet region-extracting algorithm based on image processing is proposed. By observing the recorded video, the droplet transfer process in pulsed GMAW can be divided into the two following periods:  
1. The period with an undetached droplet;
2. The period with a detached droplet.  
When in the period with an undetached droplet, the droplet is yet to detach from the wire, but eventually detaches under the actions of arc force and heat. Then, the droplet moves into the period with a detached droplet, during which the droplet is disconnected from the wire and transferred to the molten pool at a certain speed.
# A Deep Learning Approach for Network Intrusion Detection Using a Small Features Vector
## 4 Methodology  
### Dataset  
The work presented here was based on the UNSW-NB and NSL-KDD datasets. The UNSW-NB15 dataset [19] was created using Ixia's PerfectStorm ONE hardware tool in the Cyber Range Lab of the Australian Centre for Cyber Security. The tool generated modern normal and attack behaviors. The Tcp dump tool was used to capture 100 GB of raw network traffic. Argus and Bro software were used, and 12 algorithms were written to create 49 features with class labels. In total, 13 features were categorized as basic features, five were flow features, eight were content features, nine were time features, and twelve were additional features. A total of 2,540,044 records were stored in four csv files. Part of this dataset was stored as the training and testing sets with 175,341 and 82,332 records, respectively. This dataset had total 45 features. It contained a mix of numerical, binary, and nominal features. The distribution of the normal and attack packets is shown in Table 1.  
The NSL-KDD dataset is an improved version of the KDDCup99 dataset [20]. It minimized the duplicate records of the training and testing datasets. It had 43 features, of which 24 were integer type, 15 were float type, and 4 were categorical. Its KDDTrain+ dataset had a total of 125,972 records, out of which 67,342 were normal, and 58,630 were attack records. Its KDDTest+ dataset had a total of 22,544 records, out of which 12,833 were normal records, and 9711 were attack records. It had four attack classes: DoS, Probe, U2R, and R2L.
## 3 Main Methodologies
### GMM-Based APF Design
Iterate the steps (2) and (3) until \(\Delta J=\big{|}J^{(k+1)}-J^{(k)}\big{|}<\varepsilon\), \(J\) is the distortion function of K-means, written as \[J=\frac{1}{N}\sum_{j=1}^{K}\sum_{i=1,\mathbf{r}_{i}\in\mu_{j}}^{N}\|r_{ij}-\mu_{j} \|^{2}\] (16)  
The basic principle of the APF method is to construct an analytical scalar function related to states, usually composed of two types of fields: attractive potential field and repulsive potential field. Traditionally, the attractive potential field is a bowl-shaped function, while the repulsive potential field is a hill-shaped function around the restricted area. Therefore, when the object moves along the negative gradient of the potential field, it can reach the desired position without violating the path constraints. In this paper, a novel artificial potential function based on GMM is proposed. The whole potential function is expressed as  
\[\phi\Big{(}\mathbf{r},\mathbf{r}_{f}\Big{)}=\phi_{att}\Big{(}\mathbf{r},\mathbf{r}_{f}\Big{)}+ \phi_{rep}\Big{(}\mathbf{r},\mathbf{r}_{f}\Big{)}, \tag{17}\]  
where, \(\phi_{att}\) and \(\phi_{rep}\) are the attractive potential function and repulsive potential function, respectively. For the repulsive potential function \(\phi_{rep}\), it should be designed to satisfy the following properties: (1) \(\phi_{rep}\) equals zero when the service spacecraft reaches the desired position; (2) \(\phi_{rep}\) tends to infinity when the service is close to the target structural components. Therefore, based on the GMM, the repulsive \(\phi_{rep}\) is designed as  
\[\phi_{rep}=\frac{1}{2}\Big{(}\mathbf{r}-\mathbf{r}_{f}\Big{)}^{T}\mathbf{M}\Big{(}\mathbf{r}- \mathbf{r}_{f}\Big{)}\sum_{j=1}^{K}\frac{\pi_{j}}{(2\pi)^{\frac{\beta}{2}}\sqrt{ \big{|}\Sigma_{j}}}e^{-\frac{1}{2}(\mathbf{r}-\mathbf{\mu}_{j})^{T}\Sigma_{j}^{-1}(\mathbf{ r}-\mathbf{\mu}_{j})}, \tag{18}\]  
where, \(\mathbf{M}\) is a positive definite symmetric matrix. The GMM-based repulsive potential function, as shown in Equation (18), can provide a potential field for collision avoidance constrained by the complete shape of the target spacecraft without ignoring any details. It is worth noting that the GMM-based repulsive potential function is suitable for arbitrarily complex shape. The attractive function \(\phi_{att}\) is designed in the classic form [19]  
\[\gamma_{ij}=\frac{\pi_{j}p\Big{(}\mathbf{\tau}_{i}\big{|}\theta_{j}\Big{)}}{p (\mathbf{\tau}_{i}|\Theta)}.\]0  
where, \(\mathbf{P}\) is a positive definite symmetric matrix. With the novel GMM-based potential function, as shown above, service spacecraft is able to avoid collision with the target's complex shape structural components, such as solar panel and antenna, as well as to implement proximity operation.
# Dynamic Behavior and Libration Control of an Electrodynamic Tether System for Space Debris Capture
## 3 Discretized Equations of Motion
\[\mathbf{m}_{e}=\delta_{e1}m_{m}\mathbf{N}^{\mathsf{T}}\mathbf{N}\Big{|}_{\xi=-1}+ \delta_{eN}m_{n}\mathbf{N}^{\mathsf{T}}\mathbf{N}\Big{|}_{\xi=1}+\frac{l_{e}}{2} \int_{-1}^{1}\rho A\mathbf{N}^{\mathsf{T}}\mathbf{Nd}\xi \tag{28}\]  
\[\mathbf{q}_{e}^{l}=\left(\frac{4 EA}{l_{e}^{3}}\int_{-1}^{1}\left(\mathbf{d}_{e }^{\mathsf{T}}\mathbf{N}^{\mathsf{T}}\mathbf{Nd}_{e}\right)\mathbf{N}^{ \mathsf{T}}\mathbf{Nd}\xi-\frac{EA}{l_{e}}\int_{-1}^{1}\mathbf{N}^{\mathsf{T}} \mathbf{Nd}\xi\right)\mathbf{d}_{e} \tag{29}\]  
\[\mathbf{q}_{e}^{g}=\left(\frac{l_{e}}{2}\int_{-1}^{1}\frac{GM\rho A\mathbf{N} ^{\mathsf{T}}\mathbf{N}}{\left(\mathbf{d}_{e}^{\mathsf{T}}\mathbf{N}^{ \mathsf{T}}\mathbf{Nd}_{e}\right)^{3/2}}\mathrm{d}\xi+\left.\frac{\delta_{e1} GMm_{s}\mathbf{N}^{\mathsf{T}}\mathbf{N}}{\left(\mathbf{d}_{e}^{\mathsf{T}} \mathbf{N}^{\mathsf{T}}\mathbf{Nd}_{e}\right)^{3/2}}\right|_{\xi=-1}+\left. \frac{\delta_{eN}GMm_{d}\mathbf{N}^{\mathsf{T}}\mathbf{N}}{\left(\mathbf{d}_ {e}^{\mathsf{T}}\mathbf{N}^{\mathsf{T}}\mathbf{Nd}_{e}\right)^{3/2}}\right|_{ \xi=1}\right)\mathbf{d}_{e} \tag{30}\]  
\[\mathbf{q}_{e}^{d}=\left[\frac{8E\mathit{A}\mathit{a}\mathit{a}}{l_{e}}\int_{ -1}^{1}\left(\mathbf{d}_{e}^{\mathsf{T}}\mathbf{N}^{\mathsf{T}}\mathbf{Nd}_{e }\right)\mathbf{N}^{\mathsf{T}}\mathbf{N}^{\mathsf{T}}\mathbf{d}\xi\right] \mathbf{d}_{e} \tag{31}\]  
\[U=\sum_{e=1}^{N}\left(\frac{l_{e}}{4}\int_{-1}^{1}EA\xi^{2}\text{d}\xi-\left. \frac{\delta_{e1}GMm_{m}}{\sqrt{\mathbf{d}_{e}^{\text{T}}\mathbf{N}^{\text{T }}\mathbf{N}\mathbf{d}_{e}}}\right|_{\xi=-1}+\left.\frac{\delta_{eN}GMm_{n}}{ \sqrt{\mathbf{d}_{e}^{\text{T}}\mathbf{N}^{\text{T}}\mathbf{N}\mathbf{d}_{e}} }\right|_{\xi=1}+\frac{l_{e}}{2}\int_{-1}^{1}\frac{GM\rho A}{\sqrt{\mathbf{d}_ {e}^{\text{T}}\mathbf{N}^{\text{T}}\mathbf{N}\mathbf{d}_{e}}}\text{d}\xi\right) \tag{24}\]0  
The equations of motion for each element, given by Equation (27), are assembled to form the global matrix-vector equation. Subsequently, the fourth-order Runge-Kutta time integration method is applied to this equation to obtain the dynamic response of the EDT system.
###### Abstract  
A destructive Mw = 6.2 earthquake struck NW Croatia on 29 December 2020, ranking among the most hazardous events in the country in the last century. This study assesses the impact of the earthquake on the permanent geodetic stations of the Croatian national positioning system. Using a novel approach, we combined positioning station data with satellite radar data for the first time in a geodynamic study across Croatia. The analysis involved collecting daily solutions data from 11 nearby network stations as well as multi-temporal satellite images before and after the earthquake. The results reveal a significant co-seismic shift, with the Sisak reference station experiencing the largest displacement of 5 cm to the southeast. Stations up to 100 km from the epicenter exhibited horizontal shifts between 1 and 2.5 cm and vertical shifts between 2 and 4 cm. Satellite images confirmed the co-seismic effects on the permanent stations. The study establishes a strong correlation between geodetic and geological findings, suggesting that vertical displacements result from superficial deposit consolidation in the river plains due to the earthquake shaking, while positional displacement reflects tectonic block movements along the activated strike-slip fault system. The late 2020 earthquake may have further relaxed the accumulated strain on the Mt. Medvednica thrust fault system, which had ruptured in early 2020 with a lower magnitude than expected.  
earthquake; national positioning system; geodetic stations; satellite data; co-seismic displacement; active strike-slip faults Article
# Augmenting GPS with Geolocated Fiducials to Improve Accuracy for Mobile Robot Applications
## 3 Proposed Technique
Alternately this system could work effectively for a swarm of robots where periodically the robot closest to (or most underutilized) could reacquire calibration coordinates and share them with the rest of the swarm. The proposed technique shares some attributes with traditional DGPS, most notably that although there is accuracy improvement through improving common mode noise (e.g., introduced by satellites and stratosphere), non common mode noise like multipath interference around buildings will not be improved. One advantage the proposed FAGPS technique has over DGPS is that the same receiver is used for computing the calibration coordinates as what is used for navigation--so any difference in the receiver performance between a DGPS beacon and the mobile receiver is negated.
## 3 Description of Numerical Algorithms
### Krylov Subspace Methods
#### 3.4.2 Krylov-Schur Method  
A more recently proposed idea that achieves the effect of the implicit restart technique in a simpler way is the Krylov-Schur method, which is a generalization of the Lanczos thick restart [53] for non-Hermitian matrices. The method considers the Arnoldi relation (28) and applies the QR algorithm to bring matrix \(\mathbf{H}_{k}\) to its Schur form, i.e., \(\mathbf{T}_{k}=\mathbf{W}_{k}^{\mathrm{H}}\mathbf{H}_{k}\mathbf{W}_{k}\), where \(\mathbf{T}_{k}\) is an upper triangular matrix with diagonal elements the eigenvalues of \(\mathbf{H}_{k}\) (Ritz values). Subsequently, (28) becomes:  
\[\mathbf{AQ}_{k}\mathbf{W}_{k}=\mathbf{Q}_{k}\mathbf{W}_{k}\mathbf{T}_{k}+ \hat{\boldsymbol{q}}_{k}\mathbf{e}_{k}^{\mathrm{H}}\mathbf{W}_{k}\,, \tag{30}\]  
or equivalently,  
\[\mathbf{AD}_{k}=\mathbf{D}_{k}\mathbf{T}_{k}+\hat{\boldsymbol{q}}_{k} \boldsymbol{w}_{k}^{\mathrm{H}}\,, \tag{31}\]  
where \(\mathbf{D}_{k}=\mathbf{Q}_{k}\mathbf{W}_{k}\), \(\boldsymbol{w}_{k}^{\mathrm{H}}=\mathbf{e}_{k}^{\mathrm{H}}\mathbf{W}_{k}\). Decomposition (31) is reordered in order to separate undesired Ritz values from the desired ones. The part that corresponds to the desired Ritz values is kept and the rest is discarded:  
\[\mathbf{AD}_{k,d}=\mathbf{D}_{k,d}\mathbf{T}_{k,d}+\hat{\boldsymbol{q}}_{k} \boldsymbol{w}_{k,d}^{\mathrm{H}}\,, \tag{32}\]  
where \(\mathbf{D}_{k,d}\), \(\mathbf{T}_{k,d}\), and \(\boldsymbol{w}_{k,d}^{\mathrm{H}}\) represent the parts of \(\mathbf{D}_{k}\), \(\mathbf{T}_{k}\) and \(\boldsymbol{w}_{k}^{\mathrm{H}}\) that correspond to the desired Ritz values after the reordering, respectively. Subsequently, the reduced decomposition (32) is expanded to order \(k\). The above process is repeated until convergence to an invariant subspace is achieved.
# Resilience Evaluation of Multi-Path Routing against Network Attacks and Failures
## 2 Background and Related Work
### BGP Poisoning  
BGP poisoning is a rerouting technique used in BGP. By using BGP poisoning, an AS can change the routing path that it has no control over. Instead of multi-path routing, BGP poisoning can be another solution for hazards or attacks occurring in an AS that the administrator has no control. For example, Nyx uses BGP poisoning as a countermeasure for a link failure, and LIFEGUARD uses BGP poisoning to recover from a routing failure [37; 38]. However, BGP poisoning is not a standard technique. BGP poisoning can also be used as an offensive method, such as BGP hijacking [39].