esa-sceva/satcom-chunk-collection huggingface dataset:
# Compact Design of Annular-Microstrip-Fed mmW Antenna Arrays
## 3 Improvement on Multi-Directional Design  
In this part, two solutions of acquiring the characteristic of more uniform multi-directional radiation on the basis of outer annular microstrip line will be shown. More uniform multi-directional radiation does not mean better radiation characteristic but would probably be used in different usage scenarios.  
Figure 14: Radiation pattern of two-direction pitchfork-shaped microstrip antenna array (**a**) \(x\)-\(z\) plane, (**b**) \(y\)-\(z\) plane, (**c**) \(x\)-\(y\) plane.  
Figure 13: Moduli and the detailed vector plot of the instantaneous current distribution of two-direction pitchfork-shaped microstrip antenna array at around 60 GHz.
## 2 Preliminaries  
Let \(G(V,E)\) be an undirected graph, where \(V=\{v_{i}\}_{i=1}^{N_{v}}\) denotes a set of \(N_{v}\) nodes, and \(E=\left\{e_{i,j}\right\}\) is a set of edges connecting two nodes \(v_{i}\) and \(v_{j}\), i.e., \(e_{i,j}=\left\{\left(v_{i},v_{j}\right)\middle|i,\ j\in\{1,\ 2,\ldots,N_{v}\}\right\}\). In addition, let \(B=\left\{b_{i,j}\right\}\in\{0,1\}^{N_{v}\times N_{v}}\) be an adjacency matrix of \(G\), i.e., the matrix that describes the connectivity of any pair of nodes in \(V\), where \(b_{i,j}\) is assigned to one if \(v_{i}\) and \(v_{j}\), \(i\
eq j\), are connected and zero elsewhere. Let \(S=\{s_{j}|l\in\{1,\ 2,\ldots,N_{\mathrm{s}}\}\}\) be a set of \(N_{\mathrm{s}}\) speed options \(s_{l}\) to be applied to all vehicles at any node in \(G\). Suppose that there exists a group of \(N_{\mathrm{u}}\) vehicles that are assigned to visit each node in \(G\).  
Definition 1: Route and sub-route. A sub-route from \(v_{i}\) to \(v_{j}\) is defined as \(e_{i,j}\), and a route is defined as a sequence of sub-routes, i.e., \(\Xi=\left\{e_{i,j}\middle|i,\ j\in\{1,\ 2,\ldots,N_{v}\}\right\}\) that begins from the start node \(v_{i,\ start}\in V\) to the end node \(v_{i,end}\in V\). The sub-route and route that are traveled by the \(k\)-th vehicle, \(k\in\{1,\ldots,N_{\mathrm{u}}\}\), are denoted as \(e_{i,j}^{k}\in E\) and \(\Xi^{k}\), respectively.  
Definition 2: Trajectory and sub-trajectory. A sub-trajectory \(\psi_{i,j,j}\) is defined as a pair of sub-routes and speed option \(\left(e_{i,j},\ s_{l}\right)\), or in other words, the sub-route from the \(i\)-th node to the \(j\)-th node by applying the \(l\)-th speed option. A trajectory is a sequence of sub-trajectories, denoted as \(\mathbf{\Psi}=\left\{\psi_{i,j,l}\right\}\) connecting the start node \(v_{i,start}\in V\) to the end node \(v_{i,end}\in V\). The sub-trajectory and trajectory that are traveled by the \(k\)-th vehicle are denoted as \(\psi_{i,j,l^{\prime}}^{k}\), and \(\mathbf{\Psi}^{k}\), respectively.  
Definition 3: Arrival time. Arrival time of the \(k\)-th vehicle to the \(i\)-th node, denoted as \(t_{i}^{k}\), is defined as the time when the vehicle starts to enter the node.  
Definition 4: Operational time. The operational time of the \(k\)-th vehicle on the \(i\)-th node, denoted as \(t_{op}\), is defined as the difference between the times the vehicle leaves and enters the node.  
Definition 5: Completion time. A completion time, \(t_{c}^{k}\), is the time required by the \(k\)-th vehicle to visit all nodes in \(G\).  
Definition 6: Collision. Any two vehicles are said to have not collided at the \(i\)-th node if, and only if, the arrival time difference \(\left|t_{i}^{k_{1}}-t_{i}^{k_{2}}\right|>t_{op}\), \(k_{1}\
eq k_{2}\), and during the time interval each vehicle is out in the inevitable collision states defined in References [21; 22].
## 4 Results
### Process Description  
The VAM process is a realistic model since VAM is a fundamental ingredient in a wide variety of industrial and consumer products including paints, adhesives, resins, and many other. It is the product of a large-scale chemical process consisting of several basic unit operations including: a vaporizer, a catalytic plug-flow reactor, a feed-effluent heat exchanger (FEHE), a vapor/liquid separator, a gas compressor, an absorber, a CO\({}_{2}\) removal system, an azeotropic distillation column with a decanter, and a tank for the liquid recycle stream. The VAM is produced starting from fresh and recycled Ethylene (C\({}_{2}\)H\({}_{4}\)), Oxygen (O\({}_{2}\)), and acetic acid (HAc). These are converted into vinyl acetate, producing as byproducts the water (H\({}_{2}\)O) and carbon dioxide (CO\({}_{2}\)) components. The fresh C\({}_{2}\)H\({}_{4}\) stream is combined with an inert C\({}_{2}\)H\({}_{6}\) component.  
The following equations describe the functionality of the VAM:  
\[C_{2}H_{4}+CH_{3}COOH+1/2O_{2}\to CH_{2}=CHOOCOH_{3}+H_{2}O,\] \[C_{2}H_{4}+3O_{2}\to 2 CO_{2}+2H_{2}O. \tag{18}\]  
For a detailed process description, readers are referred to [14]. According to [14], the VAM process is subject to two essential safety constraints:  
* The oxygen composition must not exceed 8 mol% in the gas recycle loop. This is needed so that the process remains outside the explosivity envelope of ethylene;
* The pressure in the gas recycle loop and distillation column cannot exceed 140 psia because of the mechanical construction limit of the process vessels.  
The VAM model has been made available to a broader audience by [PERSON] et al. [39] in the form of Matlab code. It includes 246 states, 26 control variables, and 43 observed variables. Readers are referred to [39] for a complete description of the model. Figure 4 depicts the main components and control loops of the VAM process.  
Figure 5 depicts the normal operation of the VAM process (VAMP) based on a selection of two observed variables. It can be seen that the process exhibits two major states: an initialization phase, followed by a stable state.  
Figure 4: The physical architecture of the Vinyl Acetate Monomer process (VAMP) and the associated control loops (illustrated by numbers).
# Stability of Halloysite, Imogolite, and Boron Nitride Nanotubes in Solvent Media
## 2 Halloysite Nanotubes
### Colloidal Stability in Organic Media  
Another crucial aspect is the preparation of stable colloidal dispersions of halloysite nanotubes in organic media. [PERSON] et al. [63] prepared a complex of amylose and HNT by co-assembly in a  
Figure 2: Halloysite nanotubes (HNTs) and surfactant-functionalized HNT dispersions (1 wt %) in water: photographs and transmittance as a function of time. Adapted from [56].  
solid state. In particular, it was found that the amylose interacts with the outer surface of HNTs, wrapping them. The stability of pristine nanotubes and amylose-HNT dispersions in DMSO/H\({}_{2}\)O were observed for 24 h, and the precipitation of HNT occurred at 0 h [63]; whereas, since the solution of DMSO/H\({}_{2}\)O is a good dispersant for the organic moiety, the amylose-HNT was well dispersed in the solution, and no precipitation was found for 24 h [64]. This was most likely due to the interactions between amylose and the external surface of HNTs [63]. Literature also reports another strategy to obtain stable colloidal suspensions, which is the preparation of inorganic reverse micelles in non-aqueous media based on halloysite nanotubes and cationic surfactants [65]. It is known that a reverse micelle is constituted by a hydrophobic shell and a hydrophilic cavity, which create an aqueous nano-droplet in a nonpolar medium. Cationic surfactants interact with the negative outer surface of HNTs, thus creating nanoparticles with a hydrophobic jacket and a hydrophilic cavity. The action of the colloidal stability of the obtained hybrid materials was investigated in solvents with different polarity [65]. Firstly, it was observed that the length chain of the surfactant strongly influences the charge of modified HNTs. For instance, when the tail length increases, the same happens to the \(\zeta\) potential of the hybrid materials, due to the strong hydrophobic interaction between tails, as evidenced by FTIR [56]. Moreover, the hybrids present faster dynamics compared to the neat nanotubes, as evidenced by DLS (Dynamic Light Scattering) measurements in chloroform, thus reflecting the enhancement of electrostatic repulsions. The external surface of nanotubes is more hydrophobic, due to the presence of the surfactant, resulting in an increase of the colloidal stability of the nanotubes in nonpolar solvents [65]. In a few words, this procedure allows the fabricating of ecocompatible reverse micelles with different dispersibility in organic media and tunable hydrophobic/hydrophilic interfaces, thus available for industrial or biological applications.
# A New Approach to Fall Detection Based on the Human Torso Motion Model
## 3 Our Approach for Fall Detection
### The Key Concepts and Definitions in HTMM
#### 3.1.3 Centroid Height  
Centroid height means the distance from the centroid point of a person to the ground. In our approach, we adopt the hip center joint as the rough centroid of a person. There are three reasons for using the hip center joint as the centroid, rather than calculating the human shape pixels and finding out the centric position. First, the exact centroid of the human shape is not necessary for our method. The approximated point is also a good choice because of the consideration of only the descending rate of its height. Secondly, the hip touching the ground is a common scene in nearly all kinds of falls. Therefore, although the position of the hip center joint is not the exact position of the centroid of the human shape, it is more representative for fall detection. Thirdly, the Kinect software development kit (SDK) provides a set of user-friendly and effective functions to track or estimate the position of the hip center.  
Before calculating the centroid height, ground plane should be found out first. Although finding out the ground plane is a complex work, Kinect SDK provides four parameters for us, which can be used to exactly calculate the height from any points in the depth image to the ground plane. Equation (4) shows the four parameters.  
\[Ax+By+Cz+D=0, \tag{4}\]  
where \(A\), \(B\), \(C\) and \(D\) are the ground parameters that can be used to calculate point height.  
The height from the hip center to the ground \(Hc\) is calculated using Equation (5).  
\[Hc=\frac{|Ax_{c}+By_{c}+Cz_{c}+D|}{\sqrt{A^{2}+B^{2}+C^{2}}}, \tag{5}\]  
where C(\(X_{c}\), \(Y_{c}\), \(Z_{c}\)) is the hip center joint in the depth image.  
Through our experiments, we found that the centroid height can be exactly calculated by Equation (5) only when the ground is in the scene. When the Kinect sensor is installed too high to detect the ground, parameters cannot be accurately provided. All four parameters will be set to zero as their default values. Obviously, it will be a big obstacle to estimate one's centroid height. To address this issue, we use the right foot point to estimate the height of centroid when the ground parameters are zero. Therefore, Equation (5) is enhanced as:  
\[Hc=\left\{\begin{array}{ll}\frac{|Ax_{c}+By_{c}+Cz_{c}+D|}{\sqrt{A^{2}+B^{2 }+C^{2}}}&\text{ground can be detected}\\ \sqrt{\left(x_{c}-x_{f}\right)^{2}+\left(y_{c}-y_{f}\right)^{2}+\left(z_{c}-z_ {f}\right)^{2}}&\text{ground cannot be detected}\end{array}\right., \tag{6}\]  
where \(f(X_{f}\), \(Y_{f}\), \(Z_{f})\) is the position of the right foot joint in the 3D coordinate.  
Figure 5 shows the value of centroid height in two typical daily activities, crouching and walking. From the experiment data, it can be concluded that the deviation caused by calculating based on the right foot joint is acceptable.
## 1 Introduction
The electrostatic interactions between the surfactants and the clay layers do not provide an efficient linkage between the clay surface and polymer matrix. Therefore, the chemical functionalization of Mt with a silane coupling agent has attracted great attention in recent years [21]. The silylation reaction, also known as silane grafting, between the silane molecules and reactive silanol groups, located at the broken edges and at the structural defects situated at the interlayer spacing and external surface of the clay layers, is proven to be an efficient method to modify the clay surfaces [22]. The reaction of silylation is an irreversible process, because chemical bonds, with a covalent character, are formed between the silicates and organic components [23]. The silylation reaction on the internal surface of clay can cause an increase in the interlayer spacing, while the silylation taking place on the external surfaces and edges brings about a less conspicuous change, or no change, in the interlayer spacing [24]. In addition, the dispersion of the modified clay samples in the polymer matrix is improved when polymer chains are attached to the clay surfaces by covalent bonds. Polystyrene (PS) is a synthetic thermoplastic that is extensively used in various applications, due to its outstanding properties, such as high abrasion resistance, strong load bearing capacity, and convenience of processing. However, its relatively weak thermal stability greatly limits the applications in a variety of areas, such as lubricating materials in oil and gas drilling engineering. To overcome this drawback, the inorganic layered silicates have been used to enhance the thermal properties of the virgin PS [25]. To our knowledge, only a few reports described the effect of one method on the further modification by other two methods, for the alteration of Mt [26]. In this article, the triple-functionalized Mt was prepared successfully by using combined reactions of acid activation, phosphonium cation exchange, and polymerization active silane coupling agent grafting reaction. The effect of one treatment strategy on the subsequent modification by other two treatments has been investigated and compared. Furthermore, the significant role of modified Mt on the thermal stability of the polystyrene nanocomposites was extensively discussed.
# Intelligent Reception of Frequency Hopping Signals Based on CVDP
## 2 CVDP Network Design  
Figure 1 presents the block diagram of an intelligent anti-interference system designed for frequency hopping communication in a complex electromagnetic environment.  
In contrast to the traditional frequency hopping communication system, the intelligent anti-interference system of frequency hopping communication involves intelligent changes of the frequency hopping pattern by the sender. These changes are made through intelligent decision-making based on the electromagnetic interference environment to ensure uninterrupted communication. Instead of transmitting frequency hopping signals according to a predefined pattern, the sender adapts the pattern dynamically to avoid interferences. On the receiver side, a CVDP network estimates the frequency hopping sequence and achieves intelligent reception of the frequency hopping signals. The problem of predicting hopping frequency in the one-time slot is treated as a multiclassificationproblem. The CNN-GRU network designed in [27] assumes that both communicating parties have specified parameters, such as the frequency hopping period and channel bandwidth (excluding the frequency hopping sequence), and achieves estimation of multi-time slot frequency hopping sequences. However, this method has a delay for multiple time slots. In contrast, this paper primarily focuses on the estimation of frequency hopping frequency points for a one-time slot, where only the one-time slot is delayed. Furthermore, the module of the CVDP network in this paper is only used to estimate the frequency hopping frequency points. Even if the adversary employs this technology to estimate our frequency, it is difficult to effectively intercept the hopping signal without knowledge of other parameters of the unknown hopping signal.
# EdgeX over Kubernetes: Enabling Container Orchestration in EdgeX
## 5 Performance Evaluations
### Performance Change in EoK Using HPA
For example, the performance improvements with 3 and 5 concurrent requests for EoK with 2 replicas were insignificant. This indicates that when the number of concurrent requests was 3, all available CPU resources were already used. Therefore, even when we increased the number of concurrent requests to 5, there was no further improvement in throughput. In contrast, when increasing the number of concurrent requests from 1 to 3 for EoK with 4 replicas, we can see that the throughput improved significantly by fully utilizing the CPU resources for the increasing requests. Figure 7c illustrates the latency of the requests measured, which are shown in Figure 7a,b The results show that the latency tended to increase as the number of concurrent requests increased. For example, the average latency for EoK with 1 replica for each of 1, 3, and 5 concurrent requests was 250, 730, and 1270 ms, respectively. This is because the more requests are received, the longer the waiting time required for processing. However, we can also see that the waiting time decreased as the number of replicas increased. For example, the average latency for EoK with 2 replicas under 1, 3, and 5 concurrent requests was reduced to 163, 425, and 710 ms, respectively. In particular, the average latency for EoK with 4 replicas under 1, 3, and 5 concurrent requests was significantly reduced to 134, 254, and 414 ms, respectively. However, in this evaluation, it was observed that one replica with EoK yielded a marginally lower delay than that of EdgeX Foundry, and the difference in the delay of the two platforms grew with an increase in the number of concurrent requests. This is because EdgeX Foundry does not have predefined proxy settings; however, by default, Kubernetes uses iptables, which exhibit low system overhead while processing traffic. Moreover, as the autoscaling and load balancing features are absent in EdgeX Foundry, a single application service must handle all requests. Consequently, EoK outperforms EdgeX Foundry considerably. Therefore, this evaluation proves that EoK improves the latency for processing requests with load balancing among multiple replicas in Kubernetes, while EdgeX cannot. Therefore, we can conclude from our experimental evaluations that EoK can improve the service manageability and resource management through dynamic service deployment and horizontal pod autoscaling while using the existing EdgeX Foundry system as is within the Kubernetes.
# Large-Scale Automatic Vessel Monitoring Based on Dual-Polarization Sentinel-1 and AIS Data
## 1 Introduction
Generally, automatic processing algorithms require us to perform the detection over an entire SAR frame, that usually covers large geographical areas. For instance, Sentinel-1 images acquired in the Interferometric Wide Swath (IW) mode, representing the most relevant mode for the MS domain, cover a 250 km swath area. Moreover, the spatial resolution of single look complex (SLC) images is 5 m \(\times\) 20 m (range \(\times\) azimuth), resulting in images of large size. Even if such large size Sentinel-1 images are associated with complex computational resources, in this study we aim to demonstrate that processing the dual-polarization complex data for ship detection is efficient and worth. In this framework, we propose a dual-polarization coherence-based detection algorithm that can be applied to large scale SAR scenes. Our first assumption is that the ratio between the vessel signatures and the sea clutter presents high values in the coherence domain, thereby enabling a detection of vessels by applying a thresholding operation. We propose to employ the non-normalized coherence which is affected by the attenuation due to the scene-antenna distance. Therefore, for an entire SAR scene, the values of the coherence for both vessels and sea clutter vary with the range of the incidence angle, decreasing across each SAR swath from near to far range. In order to cope with this effect, we then define an adaptive threshold value for each SAR image sub-swath (i.e., three for the IW mode of Sentinel-1) in order to detect the vessels. This allows adapting the selection of the threshold as the dual-polarization coherence varies with the incidence angle and, therefore, perform a more reliable detection. The proposed algorithm can be implemented for near real time (NRT) scenarios by making use of ESA's Thematic Exploitation Platforms (TEPs) [42] or the European Commission's Data and Informaton Access Service (DIAS) [43]. As a second research objective, we perform an quantitative and qualitative analysis of the dual-polarization-based ship detection and cross-compare it with SAR intensity-based results and AIS data flows. This comparison allows us to investigate the performances of dual-polarization-based algorithm with respect to the intensity-based detections and to the vessel's size extracted from AIS data, for a large number of targets. The analysis of the experimental results is drawn from two case studies containing datasets acquired over two different geographical areas. The first one focuses on the English Channel, as an example of a dense maritime traffic area, while the second one focuses on the Mexican marine areas, containing both dense and sparse maritime traffic with reduced AIS monitoring. The paper is organized in four parts: Section 2 presents the theoretical aspects. Section 3 describes the employed datasets and presents the experimental results. Section 4 contains an extended discussion of the experimental analysis. Finally, Section 5 gives the conclusions.
# Qubit-Based Clock Synchronization for QKD Systems Using a Bayesian Approach
###### Abstract  
Quantum key distribution (QKD) systems provide a method for two users to exchange a provably secure key. Synchronizing the users' clocks is an essential step before a secure key can be distilled. Qubit-based synchronization protocols directly use the transmitted quantum states to achieve synchronization and thus avoid the need for additional classical synchronization hardware. Previous qubit-based synchronization protocols sacrifice secure key either directly or indirectly, and all known qubit-based synchronization protocols do not efficiently use all publicly available information published by the users. Here, we introduce a Bayesian probabilistic algorithm that incorporates all published information to efficiently find the clock offset without sacrificing any secure key. Additionally, the output of the algorithm is a probability, which allows us to quantify our confidence in the synchronization. For demonstration purposes, we present a model system with accompanying simulations of an efficient three-state BB84 prepare-and-measure protocol with decoy states. We use our algorithm to exploit the correlations between [PERSON]'s published basis and mean photon number choices and [PERSON]'s measurement outcomes to probabilistically determine the most likely clock offset. We find that we can achieve a 95 percent synchronization confidence in only 4140 communication bin widths, meaning we can tolerate clock drift approaching 1 part in 4140 in this example when simulating this system with a dark count probability per communication bin width of \(8\times 10^{-4}\) and a received mean photon number of 0.01.  
quantum key distribution (QKD); clock synchronization; Bayesian statistics 22 June 2021  
2021