esa-sceva/satcom-chunk-collection huggingface dataset:
# Efficient Dissemination of Safety Messages in Vehicle Ad Hoc Network Environments
## 3 The Proposed Safety Message Dissemination Scheme
### Overall Structure
The cluster consists of the cluster head (CH), which leads to the cluster and cluster members (CMs). When a vehicle detects an emergency situation, it generates an emergency safety message. This message is disseminated to nearby vehicles according to the proposed V2V safety message dissemination scheme. General safety messages are delivered based on request messages. In the proposed scheme, when the CH enters the RSU's communication range, it collaborates with the RSU to disseminate emergency safety messages. Additionally, if the CH has general safety messages needed for its cluster, it requests them from the RSU. When the RSU receives a request for emergency safety messages or general safety messages, it considers factors such as the vehicle's safety message holding rate and request rate to disseminate the safety messages.
## 3 A Service-Less Multicast Architecture for Distance Learning
### EI Enabled Multicast Architecture
```
COLD START Monitor: User ID, session ID, eNB ID Create: UE and content provider proxy for service-less multicast in eMBMS Initiate: VNF based Multicast PREDICTIVE MULTICAST Input: Timestamps, GPS, eNB IDs and SNR Apply: EI to cluster users in same eNB Cluster: Input multi-dimensional data (GPS, eNB, timestamp) to clustering algorithms Output: Geo-spatial clusters with users of same session near the same eNB in same cluster Initiate: Proactive multicast if number of users \(>\) than a threshold PROACTIVE CACHING Input: User access pattern for session, SNR, User Clusters ifUE not connected during Live session and not GPS outlier then Apply: Geo-spatial clustering to identify community members Select: A community member near to UE for caching Send: Share stream through D2D communication endif ifUE not connected during Live session and GPS outliers then From: A D2D relay between community members Send: Share stream through D2D relay endif
```  
**Algorithm 1** Pseudo code for EI enabled multicast and caching. The algorithm for geo-temporal clustering based community detection is provided in [28]. The geo-spatial clustering algorithm is a two-step framework that performs geographic clustering based on the GPS longitude and latitude points in the first step. The geographic clusters represent the edge clusters. In the second step, temporal (session timestamps) and textual data (network operator, cell ID) are used to form sub-clusters within the geographic clusters. The sub-clusters represent the users that can receive multicast traffic for the same distance learning session. Data from the UE and MNO are necessary for the implementation of the proposed EI framework. Several applications such as G-NetTrack can be utilized for the collection of network information [29; 30]. G-NetTrack collects channel-related, context-related, cell-related, and throughput related parameters. The pro version of G-NetTrack enables collection of timestamp, GPS coordinates, velocity of mobile device, operator name, cell ID, SNR, RSSI, and CQI among other parameters. The smartphone application of G-NetTrack pro can be installed on the student devices to monitor the aforementioned parameters during distance learning activities. Currently, we are in the process of collecting a large dataset from students based on distance learning classes. As a result, the proposed framework will not require any class related information from the university and multicast sessions will be created based only on UE and network level information. The evaluation in the forthcoming section evaluates the basic proposal of VNF based multicast to shed light on bandwidth and resource optimizations from the proposed work.
# Interference-Aware Radio Resource Management for Cognitive High-Throughput Satellite Systems
## 1 Introduction
* To further enhance the capacity of satellite communication systems, we firstly propose a CR-based multi-beam HTS communication architecture in this paper, where the satellite network shares the spectrum with the terrestrial network and operates in an FFR pattern. We also analyze the characteristics of this system from the perspective of large-scale antennas and multi-gateways. * We then review the challenges and design requirements of the RRM in the cognitive HTS system, which paves the way to the design of resource management. In particular, in this multi-beam satellite communication system with large-scale users, CCI comprised of inter-system CCI and intra-system CCI is the major obstacle for increasing the overall system throughput [28]. As a result, the RRM in such a complex interference scenario is a challenging problem, which is the focus of this paper. * Based on the challenges and the design requirements of RRM, we propose a joint spatial division and multiplexing (JSDM)-based RRM framework to eliminate interference with low training and feedback overhead. Simulation results are provided to validate the effectiveness of the proposed scheme, and some future research directions are also given. The remainder of this paper is organized as follows. The cognitive HTS system architecture with its details is presented in Section 2, followed by the description of design requirements of the RRM in Section 3. Section 4 introduces the proposed interference-aware RRM, and Section 5 presents the simulation results. Future research directions are shown in Section 6, and Section 7 concludes the paper.
## 2 Model
### Noise Control Parameters  
#### 2.4.1 Insertion Loss in Reflection  
The Insertion Loss (IL) is defined as the difference between sound pressure levels measured before and after a sound absorbing material is located in the path between the source and the receiver [12]. When both the source and the receiver are placed at the same side, as is our case, the concept of \(IL\) is used as in reference [14]. In this case, the original definition of \(IL\) was extended to characterize systems where only reflection and absorption (but no transmission) is allowed (Insertion Loss in Reflection, ILR).  
The magnitude of \(ILR\) of a given system is obtained by determining the acoustic pressure at different positions and frequencies, \(p(x,f)\). The measurement positions are located in front of the system to be studied. The \(IL\) is a relative parameter, comparing the acoustic pressure field scattered by the structure with respect to a reference case. In our study, a rigid wall is selected as a reference. Therefore, the definition of \(ILR\) reads:  
\[ILR[\text{dB}]\equiv L_{ref}-L_{HR}=10\log\left(\frac{|p_{ref}|^{2}}{|p_{HR}|^{2 }}\right), \tag{16}\]  
where, \(p_{ref}\) and \(p_{HR}\) are the acoustic pressures measured for the reference case and for the system of Helmholtz resonators, respectively, and \(L_{ref}\) and \(L_{HR}\) the sound pressure level in both cases.
# A Review-Unguided Optical Communications: Developments, Technology Evolution, and Challenges
## 5 Advancements in Optical Wireless Communications
### Visible Light Communication (VLC)  
The future world will be completely hyper-connected, digitized, and globally data-driven, which will make people's lives smoother and safer [258]. This can be achieved by predicting future wireless communication requirements (and their technologies), such as those beyond 5G/6G communication, the Super Internet of Things (SIOT) era, AI for data transfer, intelligent transportation systems, telehealth services, big data analytics, etc. To implement these technologies, we require a reliable and high-speed wireless connectivity. Visible light communication (VLC) technology can be used to solve this issue with a variety of advantages [259]. A VLC system transmits data by modulating light waves in the visible spectrum: 380-780 nm [260]. It covers frequencies ranging from 400 THz to 800 THz. The key concept behind this method of communication is to send data imperceptibly to human vision. Hence, humans have the illusion of a normal environment without any distinguishable change in light [261]. The advantage of VLC is that it can be simultaneously used for illumination, communication, and positioning, which is called the triple functionality of light. VLC has various features, such as its low cost, it being highly secured compared to RF systems, it receiving no interference from RF signals, no intensity interference, its spectral reusability in the adjacent channel and/or adjacent rooms, a lack of penetration through walls, and coverage extension by using spatially separated spot beams [262]. As with Li-Fi, VLC systems can be used in various fields such as in EMI sensitive areas (such as hospitals and aircraft cabins), in industrial environments with intense EM radiation (such as power plants and fabrication units), as an alternative to Wi-Fi (in living rooms, offices, shopping malls, and dense retail/public surroundings), and in smart lighting infrastructure with Internet-of-Things (IoT) applications [263]. VLC was first introduced in Japan in 2000 at the University of Keio's Nakagawa Laboratory. An indoor communication system was proposed and simulated using LEDs. In Japan, the VLC consortium (VLCC) was established in 2003 and it quickly grew into a global organization. The Japan Electronics and Information Technology Industries Association (JETTA) adopted two VLC-related standards in 2007: JETTA CP-1221 and JETTA CP-1222. The first one addresses the foundations of VLC systems and the second one is a standard for visible light identification systems. In 2013, JETTA CP-1223, an improved version of JETTA CP-1222, was approved as a standard for visible light beacons. After that, research on VLC technology expanded from a data transmission system into several other applications. Hence, the standardization of VLC technology was needed, and in 2011, IEEE
## 3 Closed-Form of Relative Energy Efficiency Based on Channel Hardening Effect  
In this section, the closed form expression of the energy efficiency is derived in the presence of the channel hardening effect.  
The frequency domain expression of the \(k\)-th subcarrier signal received by the \(i\)-th user, \(Y_{i}[k]\), is written as follows:  
\[\begin{array}{rcl}Y_{i}[k]&=&\sqrt{P_{tx}}\mathbf{H}_{i,:}[k]\zeta\mathbf{W}_ {:,i}[k]S_{i}[k]\\ &+&\sqrt{P_{tx}}\sum_{l\
eq i}\mathbf{H}_{i,:}[k]\zeta\mathbf{W}_{:,l}[k]S_{l}[ k]\\ &+&N_{i}[k],\end{array} \tag{14}\]  
where \(\mathbf{H}_{i,:}[k]\) is the \(1\times N_{t}\) channel vector of the \(k\)th subcarrier for the \(i\)th user, \(\zeta\) is the TX power normalization factor (\(\zeta\approx\sqrt{\frac{N_{t}}{K}}\)) as mentioned in Section 2.1, \(\mathbf{W}_{:,i}[k]\) is the \(N_{t}\times 1\) precoding vector of \(k\)-th subcarrier for \(i\)th user, \(S_{i}\) is the \(k\)-th subcarrier message signal for \(i\)th user, and \(N_{i}[k]\) is the \(k\)th subcarrier AWGN for \(i\)th user. The second line of (14) is the IUI term.  
From (14), the effective SINR, \(\gamma_{k}\), can be represented as follows:  
\[\begin{array}{l}\gamma_{k}[k]=\frac{\frac{P_{tx}N_{t}}{K}|\mathbf{H}_{i,:}[k ]\mathbf{W}_{:,i}[k]|^{2}}{\frac{P_{tx}N_{t}}{K}|\sum_{l\
eq i}\mathbf{H}_{i,: }[k]\mathbf{W}_{:,l}[k]|^{2}+N_{0}B},\end{array} \tag{15}\]  
where \(N_{0}B\) is the noise power in a given bandwidth \(B\).  
Then, the achievable rate of the precoded LS-MIMO can be represented as follows:  
\[\begin{array}{l}R=\delta B\cdot\sum_{i=1}^{K}E\left[\log_{2}\left(1+\frac{ \frac{P_{tx}N_{t}}{K}|\mathbf{H}_{i,:}[k]\mathbf{W}_{:,i}[k]|^{2}}{\frac{P_{ tx}N_{t}}{K}|\sum_{l\
eq i}\mathbf{H}_{i,:}[k]\mathbf{W}_{:,l}[k]|^{2}+N_{0}B} \right)\right],\end{array} \tag{16}\]  
where \(\delta\) is the scaling factor for the pilot overhead and guard interval.  
Since we deal with LS-MIMO, which has many TX antennas, an excessive amount of diversity gain can be obtained, and thus the channel hardening effect can happen and the randomness of the channel can be reduced.  
In the presence of the channel hardening effect, (16) can be simplified by using the precoding matrix in Table 1 as follows [23]:  
\[\begin{array}{l}R_{approx}^{LS-MIMO}\approx\delta BK\cdot\left[\log_{2} \left(1+\frac{P_{tx}N_{t}}{(I+N_{0}B)K}\right)\right],\end{array} \tag{17}\]  
where \(I\) is the IUI term. Note that the typical condition for (17) is \(N_{t}\geq 10K\). By plugging (17) into (6), (6) can be rewritten as follows:  
\[\begin{array}{l}EE\approx\frac{\delta BK}{P_{PA}+P_{R}}\cdot\left[\log_{2} \left(1+\frac{\eta P_{PA}N_{t}}{(I+N_{0}B)K}\right)\right].\end{array} \tag{18}\]  
To better understand the characteristics of the EE and R, we present the simulation results for the relationship between the normalized EE versus \(P_{tot}\) and normalized R versus \(P_{tot}\) in Figure 2. The normalized EE and R mean the normalized values by the value of EE and R when \(P_{tot}=10\) each. As \(P_{tot}\) increases, the normalized R increases logarithmically, while the normalized EE increases only to a certain point and then decreases.
# Reflection Enhancement and Giant Lateral Shift in Defective Photonic Crystals with Graphene
## 5 Conclusions  
We studied the reflectance of DM and the lateral shift of the reflected beam in defective PCs with graphene embedded in the center of the defect layer. High reflectivity of the DM and giant lateral shift near the DM were realized simultaneously. The interband transition of electrons in graphene greatly enhanced the reflection of the DM, and its reflectance could be as high as 0.21 for the Bragg periodic number \(N=5\). The reflectance could be further enhanced by increasing the number \(N\). Meanwhile, large lateral shift of the reflected beam was induced, and the shift could be positive or negative. The maximum of lateral shift approached the magnitude of \(10^{\circ}\lambda\) around the DM. The lateral shift could also be tuned by the chemical potential of graphene. This study paves the way for the development of highly sensitive sensors.  
Figure 7: **(a)** The lateral shift of reflected beam in the parameter space. **(b)** The lateral shift varying with the normalized frequency. The Bragg periodic number \(N=5\).  
**Author Contributions**: software, F.L. and J.W.; investigation, D.Z. and D. Z.; writing\(-\)original draft preparation, D.Z.; writing\(-\)review and editing, D.Z., P.M., S.X. and D. Z.; funding acquisition, Z.L. and D.Z.  
**Funding**: National Natural Science Foundation of China (NSFC) (61575148); Natural Science Foundation of Hubei Province (2015 CFA040, 2016 CFB515); Educational Commission of Hubei Province (D20172803); Humanities and Social Science Project of Hubei Education Department (18Q164); Colleges and Universities of National Innovation and Entrepreneurship Training Plan (201710927006Z, 201810927011).  
**Conflicts of Interest**: The authors declare no conflicts of interest.
# Application of Improved MFDFA and D-S Evidence Theory in Fault Diagnosis
###### Abstract  
To improve the accuracy of centrifugal pump fault diagnosis, a novel fault diagnosis method based on improved multiple fractal detrended fluctuation analysis (MFDFA), the fusion of multi-sensing information derived from the back propagation (BP) neural network and the Dempster-Shafter (D-S) evidence theory, is accordingly proposed. Firstly, the multifractal spectral parameters of four sensor signals under four different operating conditions were extracted as centrifugal pump fault feature vectors using improved MFDFA and input to the BP neural network. Then, the basic trust assignment function was constructed by calculating trustworthiness (both local and global) as priori information, which is based on the output results of the neural networks specific to of each group of sensors. Finally, the basic trust assignment function was fused with decision processing in accordance with the D-S evidence combination rule in order to effectively achieve the multi-sensor information fusion centrifugal pump fault diagnosis. The experimental results show the multiple fractal spectrum feature parameters extracted by the improved MFDFA can accurately reflect the signal essence, and can be used as the fault feature vector. On this basis, this multi-sensor fault diagnosis reduces the uncertainty of fault classification and demonstrates improved accuracy compared to the single-sensor fault diagnosis thanks to being based on a combination of the BP neural networks and D-S evidence theory. Thereby, this method can facilitate accurate diagnosis of the centrifugal pump fault type with high confidence, subsequently providing a novel and alternative method to existing methods of diagnosis.  
centrifugal pump; signal analysis; information fusion; BP neural network +
Footnote †: journal: Applied Physics Letters  
1
Footnote 1: Copyright** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. 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/))).
###### Abstract  
Railway embankment slopes are exposed to natural hazards such as excess rainfall, floods, earthquakes, and lake water/groundwater level variations. These are generally considered during the design, construction, and maintenance periods of the embankment. In this study, combined laboratory test methods and a computational approach were applied to assess the effect of groundwater level changes on the railway embankment. The Plackett-Burman (PBD), Box-Behnken design response surface methodology (BBD-RSM), and an artificial neural network (ANN) were used to predict the behavior of the embankment soil hydromechanical properties to determine the integrity of the embankment as water level fluctuates under varied seasonal conditions. The results show that the seepage line is concave during the rising water level (RWL) period, and the railway slope's static stability factor supes and then stabilizes. Further analysis found that the slope's stability is largely affected by some of the hydromechanical properties of the soil embankment material, such as the internal friction angle (\(\phi\)), soil density (\(\rho_{s}\)), and cohesion (\(c\)). The second-order interaction factors \(c\,x\,s\), \(x\,s\), and \(s^{2}\) also affect the stability factor. It was observed that the four most sensitive parameters under both falling water level (FWL) and RWL conditions are \(\phi\), \(\rho_{s}\), \(c\), and rate of fall/rise in water level (\(H\)). The statistical evaluation of the RSM model produced \(R^{2}\) values of 0.99(99) and 0.99, with MREs of 0.01 and 0.24 under both RWL and FWL conditions, respectively, while for ANN, they produced \(R^{2}\) values of 0.99(99) and 0.99(98), with MRE values of 0.02 and 0.21, respectively. This study demonstrates that RSM and ANN performed well under these conditions and enhanced accuracy, efficiency, iterations, trial times, and cost-effectiveness compared to full laboratory experimental procedures.  
coupled seepage-stress; static railway slope stability; prediction; perturbation analysis; artificial neural network; response surface methodology +
Footnote †: journal: Applied Sciences  
Article
# Progress in Transparent Nano-Ceramics and Their Potential Applications
## 6 Discussion
### Relationship between Nano Ceramic Materials and Biomedicine  
Nano-ceramics have been successfully employed in medical diagnoses (nano biosensors, nano bioimaging) and medical therapy (nano drug loading, nano biomedical materials, nano biocompatible organs) due to their unique sensing and biological properties. Especially, nanoceramics have great application prospects in the manufacture of biocompatible organs (artificial organs, artificial blood vessels, and artificial bones) [121]. [PERSON] et al. [122] evaluated the biocompatibility of several nano-ceramic particles (TiO\({}_{2}\), In\({}_{2}\)O\({}_{3}\), ITO, Y\({}_{2}\)O\({}_{3}\): Eu, and CuO) with bone cells, tumor cells, and hepatocytes. The results showed that the nanoparticles could be safely used in industrial and biomedical applications. [PERSON] et al. [123] found that a novel nano triphasic biocearamic composite could effectively improve the corrosion resistance and surface cell activity of orthopedic implants. Traditional medical materials and artificial organs and tissues made of various conventional materials have limited compatibility with the patient's body in clinical use, so it is difficult to fundamentally solve the disease in the patient's body. Nano-scale materials have good biocompatibility, which means they fit the structure of cells in the human body to a high degree and can successfully avoid problems such as postoperative trauma and infection [124]. At present, transparent nano-ceramics biocompatibility research and development is still limited, and there is still a long way to go before they are widely used in clinical practice. Furthermore, nanoparticles' high compatibility and degradability with blood tissue will be a long-term study focus in the future.
# Decentralized Identity Authentication with Auditability and Privacy
## 3 Overview
### Properties  
Our goal is to design and implement DID authentication protocols that achieve a good trade-off among three desirable properties.  
* Auditability: The user can detect unauthorized authentication events that use their credentials. More specifically, whenever an adversary uses stolen credentials with an honest server, this fact can be detected later on by the compromised client. Our protocols support \"passive\" detection, which is when the client detects the misuse while authenticating with an honest server, or \"active\", when the client queries the blockchain to find the misuse.
* Privacy: Given an authentication event that is logged in the blockchain, the adversary cannot link it (a) to the identity that is the subject of the authentication event, (b) to the service provider involved, or (c) to any previous authentication events triggered by the identity. We assume that in privacy attacks, the adversary can constantly observe the blockchain's content, but we leave network-level de-anonymization attacks out of the scope of this submission (i.e., the adversary cannot eavesdrop on the network connections of clients and services).
* Performance: The protocol achieves sufficient throughput to handle realistic authentication workloads.  
Table 1 compares our protocols with existing DID authentication protocols according to the three properties. We note that the first two security properties are in addition to what is provided by existing DID protocols.