esa-sceva/satcom-chunk-collection huggingface dataset:
# A Review on 5G Sub-6 GHz Base Station Antenna Design Challenges
## 3 Challenges in BSA Design
### Port Measurements: Impedance Bandwidth
#### 3.1.3 Use of Parasitic Elements  
Another method is to use parasitic elements to improve the impedance bandwidth. An octagonal loop dipole in [10] achieved an impedance bandwidth of 45%. These loop dipoles show wider impedance bandwidth compared to fundamental quarter wave dipoles. When one loop dipole is excited, the other behaves like a parasitic element to improve the bandwidth. The length of the parasitic loop element is optimized in [16] to achieve an impedance bandwidth of 52% from 1.7 to 2.9 GHz.  
In [17], an antenna array with a bandwidth of 70% from 1.32-2.74 GHz is designed. The antenna configuration is a U-shaped slot etched on each polarization leaf of the element. A parasitic element with four layers of circular metal disks is introduced to improve the impedance bandwidth. It is found that the number of layers of the parasitic elements directly improves the impedance matching. The operating principle follows the rule that the radiation resistance exhibited in a dipole is proportional to the square of the electrical length of the current path [18]. The addition of a parasitic element makes the reactance of impedance be tuned either capacitive or inductive to achieve the best match. In [19], a parasitic patch was placed above the folded dipole to enhance the bandwidth to 64.7% from 1.4-2.77 GHz. In [20], the antenna showed 63% impedance bandwidth within the 1.68-3.23 GHz range due to the parasitic element. In [40], the resonator-loaded dipole antenna with a U-shaped strip feed widened the bandwidth by moving two resonating modes closer to each other. The length of the resonator and distance between resonator and dipole is optimized to achieve a 37.5% impedance bandwidth from 0.67 to 0.98 GHz. Although inserting parasitic elements is a unique approach to solve the matching issue, it can adversely impact the radiation pattern performance.
# Experimental Study on Dynamics of Wooden House Wall Panels with Different Thermal Isolation
## 4 Dynamic Tests on Wall Panels
### Results  
During experimental tests, both models were subjected to harmonic excitations. The tests were conducted at a frequency of 2 Hz for different values of displacement amplitude. Measurements were carried out with the sampling frequency of 500 kHz using Alitce VIMEA VE 16 BCA measuring system. The exerted force was recorded by a force sensor KMM40, working in the range of up to 50 kN, the accuracy class of 0.5 and sampling frequency of 200 Hz (according to the producer's specification). The resulting displacement was measured by a laser displacement sensor optoNCDT1302, working in the range of \(\pm\)100 mm with the micrometre accuracy and sampling frequency of 750 Hz (according to the producer's specification). The force sensor was mounted at the end of the actuator's moveable rod, while the displacement sensor was installed at the actuator's shaft (see Figure 17).  
In the first stage of the tests, a wall panel with a skeleton filled with mineral wool was mounted on the stand. The results, in the form of representative hysteresis loops showing the relation between force and displacement, are presented in Figure 18. On this basis, the stiffness, \(K\), and damping ratio, \(\xi\), were calculated using the following formulas (see also Figure 19) [35]:  
\[K=\frac{F(x_{e})-F(-x_{e})}{2\cdot x_{e}} \tag{1}\]  
\[\xi=\frac{\Delta W}{2\pi\cdot F(x_{e})\cdot x_{e}} \tag{2}\]  
The results are shown in Table 5. It should also be added that the tests for this element were destructive and could not be carried out for the amplitude of displacement larger than 28 mm. For such amplitude, OSB3 sheathing began to detach from the skeleton, and connectors became loose leading to delamination of the panel (see Figure 20).  
In the second stage of the tests, a wall panel filled with the polyurethane foam was installed on the stand. Then, the experiments were carried out for the same scheme as for the panel filled with the  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Element** & **Material** & **Density [kg/m\({}^{3}\)]** & **Elasticity Modulus [GPa]** \\ \hline Frame & Wood of class C24 & 509.8 & 11—along fibres \\  & & 0.37—across fibres \\ \hline Sheathing & OSB3 & 713.8 & 1.98—along fibres \\  & & 4.93—across fibres \\ \hline Filling 1 & Mineral wool & 39 & 0.0005 \\ \hline Filling 2 & Polyurethane foam & 26 & 0.01 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Material properties of different elements used in the wooden frame house wall panels.  
Figure 21: Hysteresis loops for the panel filled with polyurethane foam.  
Figure 20: Panel filled with mineral wool after the tests.  
Figure 22: Panel filled with polyurethane foam after the tests.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Frequency [Hz]** & **Stiffness [kN/m]** & **Damping Ratio [\%]** \\ \hline
2.0 & 549.58 & 22.25 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Values of stiffness and damping ratio for the panel filled with polyurethane foam.
## 5 Results
### System Reliability Analyses for Variable Partial Factors (Sensitivity Analysis)  
Focusing on the system reliability for a reinforcement area of 4000 mm\({}^{2}\), Figure 8 shows the impact of varying the partial factors on the system safety level. Here it was visible that to ensure a safety level above the 3.8 threshold, the simple bounds (Figure 8, grey area) gave a relatively wide spectrum of possible \"minimum\" partial factors, which ranged between 1.10 and 1.17 (approximately). Furthermore, for a \(\beta\) value of 3.8, the value obtained with the MC-SuS method seemed to be close to the lower bound of the simple bounds approach with a partial factor close to 1.17. The relatively wide spectrum of the simple bounds did not enable drawing a precise conclusion about the accuracy of these \"minimum\" partial factors. However, it should be highlighted that the interpretation of this value is solely based on a \"medium\" reinforcement amount (i.e., 4000 mm\({}^{2}\)). Nonetheless, addressing other reinforcement amounts and investigating additional variations is not only relatively easy with the use of advanced computation tools but also vital to avoid unsafe decisions regarding the selection of a partial factor. Furthermore, the results of this analysis also suggested that with slightly additional computational power, the use of a variance reduction technique (i.e., level III method) might lead to even more precise results.
## 6 Discussion
The architecture of the most accurate CNN method happens to be the same for all datasets and languages (see Figure 3). Here, a notation _WE_ defines a dimensionality of word embeddings (_WE_ = 300 with fastText and 768 with BERT), and C stands for the number of classes (i.e., 2, 5, and 8 in the **chatbot**, **askUbuntu**, and **webapps** datasets, respectively). The _None_ dimension in shape tuples refers to a batch size, which, in our case, is variable (because it is among optimized parameters). Moreover, the _None_ value is presented automatically by plot_model and means that the layer can accept input of any size. Next to the CNN method architecture, architectures of LSTM and BiLSTM methods, which happen to be equally accurate, are presented: i.e., BiLSTM on the **chatbot** and **webapps** datasets with English (see Figure 4); LSTM on the **chatbot** dataset with Latvian (Figure 5); BiLSTM on the **webapps** dataset with Lithuanian (Figure 6). Figure 4: The optimal bidirectional long short-term memory method (BiLSTM) model architecture on **chatbot** and **webapps** datasets for the English language, with X1 = 800 and X2 = 300 on **chatbot** and X1 = 400 and X2 = 200 on **webapps**. Figure 3: The optimal convolutional neural network (CNN) model architecture. Since the plot_model function presents only partial information about hyperparameter values, the missing values are summarized in Appendix A. For many datasets and languages, not only the same CNN classifier and the same CNN architecture (in Figure 3) but also the same set of hyperparameter values allows us to reach the best performance. This set is presented in Appendix A with the English language, the **askUbuntu** dataset, and BERT vectorization. Since this set happened to be optimal in almost half of the best-determined models, it is recommended for various intent detection problems. Figure 5: The optimal LSTM model architecture on **chatbot** for the Latvian language. Figure 6: The optimal BiLSTM model architecture on **chatbot** for the Lithuanian language.
## 3 Satellite-to-Ground QKD Simulator
### Atmospheric Link Modeling
#### 3.2.4 Turbulence  
Scintillation effects on Free Space Optical (FSO) communication links can cause signal intensity fluctuations. These fluctuations result from thermal changes by affecting refractive indices, thus leading to beam diffraction. Turbulence-induced scintillation is categorized based on the refractive index structure parameter \(C_{n}^{2}\;(\text{m}^{-2/3})\). The value of this parameter is largely dependent on atmospheric conditions such as temperature and pressure. This study used the modified expression of the Hufnagel-Valley model [53], which considers the altitude of the ground station and the elevation angle of the link.  
\[C_{n}^{2}(h)=A_{0}exp\bigg{(}-\frac{H_{GS}}{700}\bigg{)}exp\bigg{(}\frac{H_{ GS}-h}{100}\bigg{)}5.94\times 10^{-53}\bigg{(}\frac{u_{rms}}{27}\bigg{)}^{2}h^{ 10}exp\bigg{(}-\frac{h}{1000}\bigg{)}+2.7\times 10^{-16}exp\bigg{(}-\frac{h}{1500} \bigg{)}. \tag{6}\]  
The calculation of the refractive index structure parameter \(C_{n}^{2}\;(\text{m}^{-2/3})\) requires integrating the average wind speed \(u_{rms}\) (m/s) along the slant path by employing the Bufton model [56], as well as by accounting the altitude of the ground station \(H_{GS}\) (m) and the height above the ground station \(h\) (m). The scintillation index for weak, average, and strong turbulence, when assuming a plane wave approximation following the Kolmogorov model, can be calculated using the subsequent expression [57]:  
\[\sigma_{I,pt}^{2}=\exp\left(\frac{0.49\sigma_{R}^{2}}{\left(1+1.11\sigma_{R}^{ \frac{12}{8}}\right)^{\frac{7}{6}}}\frac{0.51\sigma_{R}^{2}}{\left(1+0.69\sigma_ {R}^{\frac{12}{8}}\right)^{\frac{5}{6}}}\right)-1, \tag{7}\]  
where \(\sigma_{R}\) is the Rytov index, which, when considering the OGS's height, can be calculated as follows [53; 57]:  
\[\sigma_{R}^{2}=2.25\mathbb{k}^{\frac{7}{6}}sec^{\frac{11}{6}}(\zeta)\int_{H_{GS }}^{H_{Turb}}C_{n}^{2}(h)(h-H_{GS})^{\frac{5}{6}}dh. \tag{8}\]  
Finally, the loss (dB) induced by turbulence for a given outage probability \(p_{0}\) is calculated according to the Kolmogorov model by including the aperture averaging effect as follows [58]:  
\[L_{sci}=4.343\times\bigg{[}\text{erf}^{-1}(2p_{0}-1)\cdot\Big{[}2\text{ln} \Big{(}\sigma^{2}{}_{I}+1\Big{)}\Big{]}^{\frac{1}{2}}-\frac{1}{2}\text{ln} \Big{(}\sigma^{2}{}_{I}+1\Big{)}\bigg{]}. \tag{9}\]
## 6 Evaluation and Security
### Evaluation of Existing IoT Security Protocols  
In order to better understand the advantages of our decentralized authentication protocol based on blockchain and IPFS, we compared several scientific articles in the field of IoT security. The following table presents a comparison of several relevant articles based on different security criteria, such as authenticated encryption, replay protection, smart contract access, content integrity (IPFS), DoS resilience, and lightweight for the IoT. This analysis highlights the strengths of our approach in comparison with existing solutions.  
As shown in Table 5, our protocol offers several advantages over existing IoT security solutions. In particular, it stands out for its ability to provide authenticated encryption and effective replay protection, making it more resilient to malicious attacks. Furthermore, unlike many approaches, our solution integrates smart contracts to manage access to resources in a decentralized and transparent manner.  
Regarding content integrity, our use of IPFS ensures data protection while providing fast and reliable access, even in the event of distributed attacks. We have also considered DDoS resilience, a critical issue in IoT environments, by incorporating mechanisms that reduce the system's vulnerability to such attacks.  
Finally, our solution is specifically designed to be lightweight, making it suitable for resource-constrained IoT devices, which are often limited in terms of hardware and energy resources. This feature allows our protocol to function efficiently in large-scale IoT environments while maintaining a high level of security.
# Q-Learning Empowered Highly Dynamic and Latency-Aware Routing Algorithm for Flying Ad-Hoc Networks
###### Abstract  
With the growing utilization of intelligent unmanned aerial vehicle (UAV) clusters in both military and civilian domains, the routing protocol of flying ad-hoc networks (FANETs) has promised a crucial role in facilitating cluster communication. However, the highly dynamic nature of the network topology, owing to the rapid movement and changing direction of aircraft nodes, as well as frequent accesses and exits from the network, has resulted in an increased interruption rate of FANETs links. While traditional protocols can satisfy basic network service quality (QoS) requirements in mobile ad-hoc networks (MANETs) with relatively fixed topology changes, they may fail to achieve optimal routes and consequently restrict information dissemination in FANETs with topology changes, which ultimately leads to elevated packet loss and delay. This paper undertakes an in-depth investigation of the challenges faced by current routing protocols in high dynamic topology scenarios, such as delay and packet loss. It proposes a Q-learning empowered highly dynamic, and latency-aware routing algorithm for flying ad-hoc networks (QEHLR). Traditional routing algorithms are unable to effectively route packets in highly dynamic FANETs; hence, this paper employs a Q-learning method to learn the link status in the network and effectively select routes through Q-values to avoid connection loss. Additionally, the remaining time of the link or path lifespan is incorporated into the routing protocol to construct the routing table. QEHLR can delete predicted failed links based on network status, thereby reducing packet loss caused by failed route selection. Simulations show that the enhanced algorithm significantly improves the packet transmission rate, which addresses the challenge of routing protocols' inability to adapt to various mobility scenarios in FANETs with dynamic topology by introducing a calculation factor based on the QEHLR protocol. The experimental results indicate that the improved routing algorithm achieves superior network performance.  
FANETs; ad-hoc; reinforcement learning; UAV networks; routing protocol 2023
## 4 Conclusions  
It can be concluded that:  
* The Fenton process is an effective technology for the removal of total organic content of DAP from aqueous solutions within 120 min and 95% of TOC removal during 360 min under the following optimized conditions: 100 mg/L DAP, [H\({}_{2}\)O\({}_{2}\)] = 1000 mg/L, [Fe\({}^{2+}\)] = 50 mg/L (ferrous sulfate catalyst), and at pH = 3.2.
* The ferrous sulfate can be used effectively as a heterogeneous source of Fe\({}^{2+}\) ion and as a catalyst in the Fenton treatment of DAP from water.  
Figure 10: Proposed reaction pathway of DAP mineralization by the Fenton process.  
* A rate constant of \(7.26.10^{9}\) M\({}^{-1}\) s\({}^{-1}\) was determined for the reaction between DAP and hydroxyl radicals \({}^{\bullet}\)OH through a competition kinetic method using BA as a reference compound.
* HPLC analyses and TOC measurement indicated that numerous successive steps are involved in the degradation of DAP by Fenton oxidation including (i) oxidation via hydroxyl radicals generated from water by catalytic decomposition of H\({}_{2}\)O\({}_{2}\) in an acidic medium, (ii) oxidative opening of benzene rings into aliphatic intermediates, and (iii) fragmentation of aliphatic compounds into small carboxylic acids and then to carbon dioxide and water.
* Oxalic acid was detected as the most persistent product, being the predominant species present in the solution.
* It can be summarized that the Fenton oxidation process could be the best method for the total destruction of DAP from water.  
[PERSON] and [PERSON] designed the experimental part; [PERSON] and [PERSON] performed the experiments; [PERSON] and [PERSON] supervised experimental work and data analysis; [PERSON], [PERSON] and [PERSON] wrote the manuscript.  
The publication of this article was funded by the Qatar National Library.  
All authors of this article declare no conflicts of interest.
# A Police and Insurance Joint Management System Based on High Precision BDS/GPS Positioning
## 2 Related Work
However, these methods have deficiencies such as inadequate data accuracy, insufficient sensor fusion, single evidence chain and being non-authoritative. Therefore, this article targets the development of an intelligent terminal based on high precision BDS/GPS positioning. The terminal integrates a GPS/BDS chip, inertial sensor, network communication and other devices that it can obtain enough data for the analysis of vehicle behaviors. As for the analysis of vehicle behaviors, most researches and analyses are conducted from the aspects of the long-term driving habits and driving risk assessment [16; 17; 18], but not from the aspects of claims, accident assessment and responsibility identification. This article addresses accident claims, and rapid accident responsibility identification and damage assessment. This requires accurate judgement of lane level behaviors in order to achieve accurate vehicle behavior statistics and remote accident responsibility identification. The key point to realize the above function is to apply high precision positioning. Some researchers, such as [PERSON] et al., [PERSON] et al., and [PERSON] et al., proposed to have built-in integration of multi-sensor equipment such as RTK, PPP, accelerometers, gyroscopes and magnetometers to improve the positioning accuracy and the calibration accuracy of the equipment [19; 20; 21]. [PERSON] et al. suggested applying wide area precise positioning in vehicle network systems and the development of a concurrent service system with a flexible virtual extension framework to ensure reliable data exchange between the vehicle and the background, so as to realize a lane level positioning service [6]. The server can broadcast satellite-enhanced signals. Researchers utilize the signal to conduct error analysis and data processing in the space segment, communication segment and user segment of BDS/GPS satellites [22]. Thus they enhance the satellite positioning accuracy to sub-meter level for mass applications; additionally, they achieve multi-sensor fusion in the equipment and apply wide area real-time precision positioning to the vehicle network system. Therefore, they can realize high precision seamless positioning in the city after they break through various space-time barriers and solve the problem of the lack of information in location-based services. In conclusion, the accuracy of satellite positioning to sub-meter level in mass applications can be realized. In addition, it is feasible to meet the requirements of both responsibility identification and damage assessment for vehicle insurance and evidence collection for public security and traffic administration departments.
# 5G V2X System-Level Architecture of 5 GCAR Project
###### Abstract  
One of the goals of the 5G Communication Automotive Research and innovation (5 GCAR) project has been to evaluate and propose system architecture enhancements aiming at supporting the strict requirements of vehicle-to-everything (V2X) use cases. In this paper, we provide an overview of 3 GPP 5G system architecture, which is used as a baseline architecture in the project, and we present the main architectural enhancements introduced by 5 GCAR. The work of the project focused on the following categories: (i) end-to-end security, also including aspects of privacy; (ii) network orchestration and management; (iii) network procedures; (iv) edge computing enhancements; and (v) multi-connectivity cooperation. The enhancements introduced by 5 GCAR to above-listed categories are discussed in this paper, while a more detailed analysis of some selected features is presented.  
V2X; 5G; QoS; system architecture +
Footnote †: journal: _Future Internet_  
0000-0001-1000-1000-10001-10000-10001-10000-10000-10000-10000-1000-10000-1000-  
the current architectural conception. The general technical challenges brought by vehicular applications were summarized in four main technical areas: (i) V2X main characteristics (mobility and simultaneous requirements for massive numbers of ultra-reliable, low latency, high bandwidth communications); (ii) multiple access network connectivity (including the management of multiple network slices); (iii) resilience requirements, security, and data privacy; and (iv) roaming between operators. 5 GCAR proposed a collection of enhancements, referred to as \"technical components\", designed to address specific needs and requirements of automotive applications. The introduced enhancements focus on optimized end-to-end V2X network connectivity for highly reliable and low-latency V2X services, security and privacy, (Quality of Service) QoS and traffic flow management in a multi-Radio Access Technology (RAT) and multi-link V2X communication system [7]. The contribution from 5 GCAR project has been to address enhancements that can be mapped to 3 GPP system architecture, i.e., proposed technical components can be considered as add-ons to be integrated into already defined 3 GPP network functions. Above mentioned technical components were grouped into five different categories:  
* end-to-end security;
* network orchestration and management;
* network procedures;
* edge computing enhancements;
* multi-connectivity cooperation.  
The aim of this paper is to present the outputs of the studies performed by 5 GCAR on the system architecture.  
The remainder of the paper is structured as follows. Section 2 summaries the 3 GPP 5G system architecture, which has been used as a baseline within 5 GCAR. Section 3 provides an overview of the overall 5 GCAR architecture design, in which Section 4 offers a more detailed description of some selected components. Finally, Section 5 provides conclusive remarks.