esa-sceva/satcom-chunk-collection huggingface dataset:
# Millimeter-Wave Smart Antenna Solutions for URLLC in Industry 4.0 and Beyond
## 5 Research Opportunities and Future Directions
### mmWave Antenna Array Design Challenges
In order to make a robust and efficient smart antenna system, the smart antenna systems should entail rigorous RF measurements in real industrial environments. This will help to fully characterize the propagation channels of industrial wireless systems over the mmWave band.
## 2 Data Set and DSM Preparation
### Remote Sensing Data
The HRSC camera was originally designed and developed for the Mars Missions [39], but one camera version has been used for land cover monitoring applications [38]. The DSM used in this study (displayed in Figure 2c) was provided by the Institute of Space Sensor Technology and Planetary Exploration, German Aerospace Center (DLR). The data set from 2012 was prepared using the SGM method as in the case of the satellite images, but was generated with the remote sensing software package Graz (RSG) [37]. The DSMs delivered from RSG included gaps, i.e., unmatched pixels, which were filled with the same method used for the satellite images [34]. We refer to the DSM generated from these data as Aerial2012 (Figure 2h). All data sets were converted and co-registered to the geographic reference system of the Bavarian State Forest Administration, which is the German Gauss-Kruger coordinate system, zone 4. The LiDAR2010 DSM was chosen as reference for the co-registration. The co-registration procedure is described in [34] and leads to accuracies of half a pixel. As the shifts among these data sets are very small, only linear shifting is considered. We use a simple version of least square matching. Figure 2: DSMs generated from three active systems (LiDAR2001 (**a**), LiDAR2010 (**b**), TanDEM-X2013 (**i**)) and six passive, optical systems (HRSC2003 (**c**), ALOS2008 (**d**), Cartosat2008 (**e**), RapidEye2009 (**f**), WorldView2012 (**g**) and Aerial2012 (**h**)), the ellipses in (**a**,**b**) mark the region that was destroyed by the storm Kyrill in 2007. The shift distances in three dimensions are estimated via iterative 3D shifts adjustments based on the minimization of the summarized squared height difference. Instead of using the whole image, we have manually selected some ground regions for the calculation. The calculated shifts in each of the three directions are documented in Table 2. To compare the datasets at pixel-level, all DSMs displayed in Figure 2 were resampled to a resolution of 2.5 m.  
As mentioned above, some parts of the Traunstein forest were affected by a windthrow in 2007. The forest regions that were damaged are clearly visible by comparing the two LiDAR DSMs. The main affected area is marked by an ellipse in Figure 2a,b. This change in the forest structure can also be seen in all other DSMs captured after 2007.
## 3 Proposed Online Fault Diagnosis Model
### Proposed New Fault Mode Detection
#### 3.3.1 k-Means Clustering  
\(k\)-means clustering is the simplest unsupervised clustering algorithm and has been adopted in several application domains [35; 36]. In \(k\)-means clustering, \(k\) centroids are initially selected at random, and data samples \(\{x_{1},\,\dots\,x_{n}\}\) are assigned to disjoint clusters corresponding to the nearest centroid based on a clustering criterion function \(F\)[19], which is generally the squared distance between each sample \(x_{i}\) and the centroid \(c_{j}\) of cluster \(C_{j}\), as given in Equation (6)  
\[F(c_{1},\dots,c_{k})=\sum_{j=1}^{k}\sum_{i=1}^{N_{j}}\|x_{i,j}-c_{j}\|^{2} \tag{6}\]  
where \(c_{1}\,\dots\,c_{k}\) are the centroids of clusters \(C_{1}\,\dots\,C_{k}\), respectively, \(k\) is the total number of clusters, and \(N_{j}\) is the total number of samples assigned to the \(i\)th cluster. After data samples are assigned to clusters, centroids are relocated based on their membership information.  
This process is repeated until there is no change in the value of \(F\)[37]. Since the \(k\)-means clustering algorithm is sensitive to the \(k\) initial centroids, it may converge to a suboptimal solution [20; 38]. Many algorithms have been devised to reduce the sensitivity of the process to \(k\), but they inevitably increase the computational cost or introduce new variables. In this study, we use the initial centroid selection method of [PERSON] [20], which considers the deepest valleys and highest gaps between clusters in a dataset. This algorithm sorts the data samples in ascending order of their magnitude \(d_{1},\,\dots\,d_{n}\), then calculates the Euclidean distance between each pair of consecutive points, \(D_{i}=\mathit{dist}\,(d_{i}-d_{i+1})\), where \(i=1\,\dots\,n-1\). Next, the distances \(D_{i}\) are sorted in descending order while keeping their original indices \(i\) for identifying the position numbers after further processing. The algorithm selects the first \(k\) - \
# Functionalization Strategies and Fabrication of Solvent-Cast PLLA for Bioresorbable Stents
## 3 Results and Discussion
### BRS Obtained by the Solvent-Cast Direct Write Technique  
The solvent-cast high molecular weight PLLA activated with plasma or enzymes presented an appropriate crystallinity, molecular weight, degradation rate, and enhanced ECs response which makes it a biomaterial suitable to be used for BRS fabrication. As a proof of concept, PLLA BRS stents were fabricated by the solvent-cast direct-write technique to assess its feasibility. Tubular structures of 5 mm diameter and 20 mm length (Figure 8) were obtained. Perfectly regular and seamless stent structures were obtained, with a regular monofilament diameter of \(\approx\)150 \(\upmu\)m. The junctions were properly welded leading to a flexible and resistant prototype.  
The stent design, following a hombohedral pattern, was selected in order to obtain a welded structure with appropriate mechanical properties to expand and deploy into the artery. The design should ideally minimize the quantity of material in contact with the blood stream to avoid blood turbulence, as this may lead to LST. Moreover, its design also plays a role in its degradation rate. The in vitro degradation rate of a device is affected by several factors such as the material composition, pH, molecular weight, or device geometry, etc. Since the experimental research for an optimal device can be time-consuming, mathematical models of interest regarding the in vitro degradation rate of devices can be found in the literature [68]. The degradation of PLLA consists first, in a chemical hydrolysis where water breaks the hydrolysate bonds and secondly, the resulting degradation products are removed by the organism. The previous considerations allow introducing the concept of safe-by-design to our stent in order to minimize the risk of the polymeric nano-biomaterials degradation products of PLLA when delivered in the bloodstream and enhancing the device safety [68; 69].
# Research on Optimization of Target Positioning Error Based on Unmanned Aerial Vehicle Platform
## 3 Error Transmission Theory
### Error Transfer from Airframe to Geographic Systems  
For the airframe system coordinates \(A_{h}=(x_{h},y_{h},z_{h})^{T}\), \(A_{h}\sim N(\mu_{h},P_{h})\); the UAV attitude angle \(\Psi=(\phi,\theta,\sigma)^{T}\sim N(\mu_{\Psi},P_{\Psi})\), where \(\mu_{\Psi}=(\overline{\phi},\overline{\theta},\overline{\sigma})^{T}\), and the diagonal matrix \(P_{\Psi}=diag(\rho_{\phi}^{2},\rho_{\theta}^{2},\rho_{\theta}^{2})\) can be obtained by transforming the geographic system coordinates \(A_{n}=(x_{n},y_{n},z_{n})^{T}\).  
The coordinate transformation is represented as follows:  
\[\begin{bmatrix}x_{n}\\ y_{n}\\ z_{n}\end{bmatrix}=\begin{bmatrix}\cos(\varphi)&\sin(\varphi)&0\\ -\sin(\varphi)&\cos(\varphi)&0\\ 0&0&1\end{bmatrix}^{-1}\begin{bmatrix}\cos(\theta)&0&-\sin(\theta)\\ 0&1&0\\ \sin(\theta)&0&\cos(\theta)\end{bmatrix}^{-1}\begin{bmatrix}1&0&0\\ 0&\cos(\sigma)&\sin(\sigma)\\ 0&-\sin(\sigma)&\cos(\sigma)\end{bmatrix}^{-1}\begin{bmatrix}x_{h}\\ y_{h}\\ z_{h}\end{bmatrix}\Bigg{|}_{\Psi=[\overline{\phi},\overline{\theta},\overline{ \sigma}]} \tag{7}\]\[P_{n}=(I_{h}^{n})P_{\Psi}(I_{h}^{n})^{T} \tag{8}\]  
where  
\[I_{h}^{n}=\begin{bmatrix}\frac{\partial x_{\Psi}}{\partial\theta}&\frac{\partial x _{\Psi}}{\partial\theta}&\frac{\partial x_{\Psi}}{\partial\theta}\\ \frac{\partial y_{\Psi}}{\partial\theta}&\frac{\partial y_{\Psi}}{\partial \theta}&\frac{\partial y_{\Psi}}{\partial\theta^{\prime}}\\ \frac{\partial z_{\Psi}}{\partial\theta}&\frac{\partial z_{\sigma}}{\partial \theta}&\frac{\partial z_{\sigma}}{\partial\theta}\end{bmatrix}_{\Psi=\mu_{ \Psi}} \tag{9}\]
## 4 Results
### Complexity and Cost Analysis of OrthoDETR  
In this section, we provide an in-depth analysis of the complexity and cost associated with implementing our proposed OrthoDETR method. Understanding these factors is essential to evaluate the practicality and efficiency of our method for real-world applications.
## 3 Underwater Communication Experiment and Discussion
The processed optical signal is converted into an electrical signal using the APD130A2 avalanche photodetector produced by Thorlabs (Newton, NJ, USA). This detector has a receiving threshold of \(-\)46 dBm and a response range of 200-1000 nm. The APD output signal is then detected by an oscilloscope to show a modulation frequency of 10 MHz and sampled by the ACM9238 at a sampling rate of 65 Msps, then converted to a digital signal and demodulated, decoded, and otherwise processed by the FPGA. Finally, the signal processed by the FPGA is displayed by the host computer through the AXI protocol. After the system construction was completed, picture transmission was tested at a communication rate of 10 Mbps. Figure 8a shows the diagram of the upper computer sending the picture. The picture information is processed by the transmitter and modulated onto the laser beam for transmission through a 10 m underwater channel. Figure 8b illustrates the received picture on the upper computer at the receiver end. The results demonstrate that the system successfully achieved reliable picture information transmission. After completing the infor  
Figure 7: Components of the UWOC experimental platform. (**a**) System test platform, (**b**) transmitter composition, and (**c**) receiver composition. mation transmission test, the performance of each signal processing module in the system was further tested and analyzed in depth, and the results were as follows.
# Frequency Selective Surfaces: Design, Analysis, and Applications
## 3 Elements of Frequency Selective Surfaces  
Frequency-selective surfaces can be broken down into three major configuration classification: namely, element-based FSSs, structure-based FSSs, and application-oriented, as shown in Figure 5. Traditionally, FSSs were made of resonant elements with dimensions comparable with the wavelength at the operational frequency. In such structures, an array of metallic elements is illuminated by a plane wave that stimulates the electric current on elements. The amplitude of the induced current depends on the strength of coupling between the elements and the wave, while the highest level of coupling occurs at the fundamental frequency, where the length of the element is \(\lambda/2\). The frequency response of the FSS is determined by the distribution of the electric current on elements, dependent on the element's shapes. Since the resonance in traditional FSSs is dependent on the length of the unit cell, the excitation of higher-order resonance modes is unavoidable. As an indication, the current distribution along a single element of a resonant FSS is presented in Figure 6, showing the distribution of current for the fundamental resonance and its first harmonic. Some specific harmonics of FSSs are excited under oblique incidences. Thus, the frequency response might be highly degraded under oblique incidence.  
Figure 5: Classification of FSSs.  
Figure 6: Current distribution at the first and the second resonant modes—**(top)** shows the fundamental mode (frequency \(f_{0}\)), which is excited for any element shape irrespective of the incidence angle; **(bottom)** shows the first odd mode at about \(2f_{0}\), which may be excited at oblique incidence. The frequency of this mode may change slightly depending on the element shape [1].  
Even though the geometry of elements has a major impact on filtering, other parameters such as the dielectric properties of the substrate supporting the elements and the spacing between them also influence the frequency of operation and the bandwidth. For a better understanding of the FSS operation, it is essential to understand the structure of FSSs. Here, we study the main unit cell geometries used in the design of traditional resonant FSSs [111]. The four major categories of the unit cells used in the traditional designs are as follows:  
1. N-poles or center-connected, such as dipole, three-legged element or tri-poles, Jerusalem cross, cross dipoles, and the square spiral, as shown in Figure 7a.
2. Loop types, such as the three- and four-legged loaded elements, the circular loops or rings, square, and hexagonal loops, as shown in Figure 7b.
3. Solid interiors or plate types mainly in patch or aperture forms, i.e., square meshes and circular patches, as shown in Figure 7c.
4. Combinations or sophisticated patterns, i.e., combination of solid interior shapes or center-connected loops to overcome the deficiencies with simple shaped elements as shown in Figure 7d.  
The four groups of the unit cells are discussed in the following sub-sections.
## 5 Gestac_App-Gestac Model Prototype
### Architecture  
The GESTAC prototype was implemented as a web application in order to achieve the model's goal of sharing knowledge across different users from different places within a business domain. Figure 7 shows a diagram of the GESTAC prototype architecture, and Figure 8 the back-end design. The front-end (Figure 7) should act as the interface with the previously logged on user, where the browser is located on the client device. The back-end contains the services that are used by the front-end to perform functions, including data processing, data storage and system logic. The front-end and back-end are connected by means of a network that may be located on the same device (when the front-end and back-end are together) or a local area network (via intranet in connections at the same company) or via the Internet (in wide area connections). As shown in Figure 8, we used the criterion of separation into three layers for the back-end design: web layer, responsible for all the services, domain layer, responsible for the operational logic, and the data storage access layer. The WEB module contains the presentation and business layers. The presentation layer has all the application's front-end web behavior. It uses web pages that were implemented in JSP (JavaServer Pages), HTML (Hypertext Markup Language), CSS (Cascading Style Sheets), JavaScript, AJAX (a set of web development techniques using many web technologies on the client side to create asynchronous web applications). The web module business layer was implemented using servlets to respond to the requests launched from the presentation layer using web pages. The business logic is executed, and the data access objects (DAO) in the persistence layer are used by the persistent entities to communicate with the database. Filters were used to filter the authorization of the requests from the front-end and web resources when the user is not logged on, controlling that the only access point is the login page. Each request is mapped to the servlet that processes and executes the logic specific to the action requested for the web page. The interface, where Hybernate will be used for data persistence, defines the basic administration methods and a class implementing the methods.  
Figure 7: GESTAC prototype architecture.
# Collaborative Caching for Implementing a Location-Privacy Aware LBS on a MANET
## 2 Related Works
### Collaborative Caching in Continuous LBSs  
Although our work focuses on sporadic queries, continuous LBSs research has developed several relevant caching concepts that we adapt to our privacy-preserving MANET environment. [PERSON] et al. [11] proposed a P2P-based collaborative cache architecture that significantly reduces performance degradation by filtering candidate responses. We adapt this filtering concept for our MANET environment but distribute the filtering responsibility across mobile nodes rather than relying on fixed peers. [PERSON] et al. [12] combined Markov models with k-anonymity, using mobility predictions to improve cache efficiency when responses are not found locally. While effective for predicted trajectories, this approach's dependence on movement patterns limits its applicability in our more dynamic MANET context.  
[PERSON] et al. [13] advanced the field by developing a system that only requires the prediction of the next location, reducing the complexity of the prediction of the trajectory. However, their approach still depends on predetermined trajectories, unlike our solution, which accommodates arbitrary movements. [PERSON] et al. [14] introduced a particularly relevant two-level cache system with user caches supplemented by an anonymizer cache. Although this hierarchical approach influenced our design, we eliminated their centralized anonymizer, instead distributing this functionality across MANET nodes to enhance privacy protection and system resilience.
# Improvement of 5G Transportation Services with SDN-Based Security Solutions and beyond 5G
## 2 Literature Review and Related Work
### Intelligent Approach to Secure Solutions  
There are many transportation services in 5G applications, such as driver safety. Although methods of measuring network traffic flow based on the transportation services within the specific application are the same, different types of data and channel conditions, etc., vary the data rate and other aspects of performance such as delay. Connected and intelligent transport systems based on 5G will continue to rely on ubiquitous broadband connectivity. Future public safety of transport services depends on the emerging technology based on 5G and beyond. Our proposed framework enhances the required services through the connected and intelligent system. The novelty of the framework is that maximizing the secure services with minimum cost depends on the energy and complexity of the overall technology. When the end-users in the transport sector define future requirements and solutions, this novelty will be maintaining intelligently and proactively with the emerging technologies. The transport system may enhance their existing feature or add entirely new features in future services. Using a lower band of spectrum (THz) for limiting the frequencies through 5G+ allows us to utilize the intelligent reconfigurable system in future transport services.  
The collaborative 5G-based spectrum management and sharing and artificial intelligence (AI) enable the transport sector to improve its services. Using connected and intelligent systems, future Intelligent Transportation Systems (ITS) services become more cost-efficient, secure, and sustainable. Due to new requirements arising in ITS, traffic efficiency is one of the challenges during the safety management of the transportation system. Safety-related data often require Ultra-Reliable and Low-Latency Communications (URLLC). For instance, the infotainment category with sensors (vehicle-as-a-sensor) requires high data-rate connections between vehicles or between vehicles and the cellular network at high vehicle speeds and dynamic interference conditions [18]. To improve the 5G+ transportation system, the URLLC enhances the rate of the VCS of the ITS and C-ITS. Despite the recent and ongoing enhancements to 5G+ transportation services, this paper [18] supports us to create the mathematical formulation for the intelligent value obtained from the user data traffic and other network parameters such as rate considered in the transportation services.
# A Novel Energy-Efficient Contention-Based MAC Protocol Used for OA-UWSN
## 1 Introduction
Meanwhile, Reference [18] proposed a scheme based on time division multiple access (TDMA), where the sink node detects its distance from all neighboring nodes and notifies all nodes of the scheduling transmission sequence through superframes. Reference [19] proposed a slotted floor acquisition multiple access (S-FAMA) protocol, which divides time into slots. All packets must be transmitted at the beginning of each time slot, so that collisions can be avoided. In a contention-based MAC protocol, all nodes equally access the channel through competition. Reference [20] proposed that in an ordered carrier sense multiple access (CSMA), the scheduler notifies all nodes of the transmission schedule so that each node knows when to transmit information. Reference [21] proposed a low-energy MAC protocol (T-Lohi), which contends for the channel by sending a short frame. If there is only one node competing, then the data can be transmitted. Otherwise the competing node waits and then competes again. At present, underwater optical communication generally uses blue-green light in the visible light band for data transmission. However, UWSN research based on underwater optical communication is full of challenges. In particular, there is great need for an efficient MAC protocol. This paper proposes a novel optical-acoustic competitive MAC protocol (OA-CMAC) based on the underwater optical-acoustic hybrid wireless sensor network in our previous work. The protocol combines the advantages of fast transmission, low loss, high bandwidth of underwater optical communication, and long-distance propagation of underwater acoustic communication [11]. Based on optical-acoustic fusion technology, it uses the postponed access of carrier sense multiple access with collision avoidance (CSMA/CA) technology to achieve high-speed and reliable transmission of underwater data while ensuring channel utilization and energy efficiency.