esa-sceva/satcom-chunk-collection huggingface dataset:
# A Survey of Analog-to-Digital Converters for Operation under Radiation Environments
## 4 Data Analysis  
As advanced in Figure 1, the selection described in Section 3 is analyzed and compared with designs presented at the IEEE ISSCC (International Solid-State Circuits Conference) and the VLSI (Symposia on Very Large Scale Integration Technology and Circuits) from 1997 to 2019. These designs are considered the state of the art of scientific ADCs in this analysis. From now on in this section, the former population of ADCs is referred as the _selection_ and the latter as the _state of the art_.  
The presented analysis aims to extract patterns of the power efficiency of radenv-ADCs. Unfortunately, it cannot be warrantied that all collected data were measured with the same criteria; consequently data presented in Table 1 could be slightly shifted. This is specially critical for radiation data, as will be explained in Section 4.3. However, this fact will have little impact on the final conclusions about patterns and performance envelopes of radenv-ADCs.  
Data from Table 1 are represented in several ways in Figures 2-8 to extract different patterns of the _selection_; the envelope defined by the best performing specimens is depicted with a dashed line in each figure. Additionally, the envelope defined by the best performing specimens of the _state of the art_ is represented with a solid line in Figures 2-5. Detailed data about each specimen and envelope of the _state of the art_ can be found in [15]. Furthermore, we have discerned data by ADC architecture using different symbols (cf. legends).  
Figures 2, 3 and 5 present envelopes shaped alike for both the _selection_ and the _state of the art_; the same behavior is observed in Figure 4 up to 100 MHz. These facts endorse the assumptions that patterns between both populations can be compared and that conclusions from this comparison can be extracted considering that the main difference between both populations is the radiation hardening feature.  
Inferred data in Figures 2-5, 7 and 8 are marked with a black round circle around their symbolic representation. Since inferences could be slightly improved with regard to measures, the former are not considered to establish the envelopes in those figures. In any case, only one case with inferred data (ADS1258) is close to the envelopes.
## 3 Results
### Accuracy of the Detection of the Analyzed Land Cover  
Tables 3 and 4 detail the accuracy of the recognition of lakes through spectral indices and land cover. Accuracy was measured by means of producer accuracy, user accuracy, overall accuracy and Kappa index. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline  & \multicolumn{3}{c}{**Pearson’s \(r\) in 2000**} & \multicolumn{3}{c}{**Pearson’s \(r\) in 2010**} & \multicolumn{3}{c}{**Pearson’s \(r\) in 2020**} \\ \hline  & NDWI & MNDWI & AWEI & NDWI & MNDWI & AWEI & NDWI & MNDWI & AWEI \\ \hline NDWI & 1.00 & 0.95 & 0.80 & 1.00 & 0.97 & 0.85 & 1.00 & 0.98 & 0.88 \\ \hline MNDWI & & 1.00 & 0.93 & & 1.00 & 0.90 & & 1.00 & 0.88 \\ \hline AWEI & & & 1.00 & & & 1.00 & & & 1.00 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Spectral indices using Pearson’s \(r\). \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline
**Years** & **Class** & **UA (L)** & **UA (V)** & **PA (L)** & **PA (V)** & **OA (L)\%** & **OA (V)\%** & **Kappa (L)\%** & **Kappa (V)\%** \\ \hline \multirow{8}{*}{2000} & W & 95 & 90 & 94 & 90 & 88 & 85 & 87 & 80 \\ \cline{2-9}  & C & 85 & 82 & 85 & 82 & & & & \\ \cline{2-9}  & Mo & 94 & 91 & 94 & 89 & & & & \\ \cline{2-9}  & Pr & 89 & 84 & 91 & 83 & & & & \\ \cline{2-9}  & S & 91 & 80 & 88 & 85 & & & & \\ \cline{2-9}  & We & 90 & 83 & 87 & 84 & & & & \\ \cline{2-9}  & PF & 80 & 85 & 84 & 80 & & & & \\ \hline \multirow{8}{*}{2010} & W & 96 & 94 & 95 & 90 & 90 & 86 & 91 & 85 \\ \cline{2-9}  & C & 85 & 78 & 86 & 83 & & & & \\ \cline{2-9}  & Mo & 92 & 88 & 96 & 92 & & & & \\ \cline{2-9}  & Pz & 87 & 80 & 93 & 88 & & & & \\ \cline{2-9}  & S & 92 & 88 & 85 & 80 & & & & \\ \cline{2-9}  & We & 95 & 85 & 90 & 85 & & & & \\ \cline{2-9}  & PF & 90 & 85 & 85 & 80 & & & & \\ \hline \multirow{8}{*}{2020} & W & 93 & 87 & 95 & 88 & 85 & 83 & 88 & 83 \\ \cline{2-9}  & C & 83 & 81 & 85 & 80 & & & & \\ \cline{2-9}  & Mo & 88 & 84 & 90 & 85 & & & & \\ \cline{2-9}  & Pr & 88 & 82 & 92 & 85 & & & & \\ \cline{2-9}  & S & 89 & 80 & 87 & 83 & & & & \\ \cline{2-9}  & We & 93 & 87 & 92 & 88 & & & & \\ \cline{2-9}  & PF & 85 & 80 & 88 & 83 & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Accuracy of lake and land-cover classification using the SVMs classifier.
# Recent Advances in Spectroscopy Technology for Trace Analysis of Persistent Organic Pollutants
## 3 Conclusions and Prospects  
In this work, recent advances in spectroscopy technologies, such as SERS, SPR, and fluorescence for trace detection of POPs were summarized. It has been demonstrated that high sensitivity and selectivity can be obtained by designing elaborate nanostructures for the substrates and improving specificity and affinity for targeted molecules. The investigations of these achievements could support some novel strategies for monitoring various environmental pollutants in the future.  
Nowadays spectroscopy technology is confronted by some challenges in the practical implementation of low-level detection of POPs with complex samples. Though great efforts have been  
Figure 6: (**A**) SEM images of the lateral view and top view (inset) of TiO\({}_{2}\) NTs (a) and CdTe-TiO\({}_{2}\) NTs (b). (**B**) Schematic representation of photo-induced electron transfer mechanism for fluorescence quenching of g-(N,N-diphenylcarbamoyl)propyltriethoxysilane (DPTES) by PCB77. Republished with permission from [82; 86] (Copyright © 2014, Elsevier; Copyright © 2010, American Chemical Society).  
made to enhance sensitivity and reproducibility, some problems still exist in the reliable analysis of ultratrace concentration and eliminating the interference of other coexisting pollutants. Thus, great attention still should be given to these problems to achieve a higher sensitivity and more accurate monitoring of POPs in complex matrices. Furthermore, the coupling of spectroscopy technologies with other methods will be much better for separation of coexisting pollutants and providing comprehensive and accurate information of targeted molecules during the whole experiment. We anticipate that it will be a popular trend in the future. Continued investigations in this field will significantly improve the practical applications of spectroscopy technologies in the trace analysis of various environmental pollutants.  
[PERSON] conceived and wrote this manuscript; [PERSON] and [PERSON] provided guidance and suggestions for this manuscript. All authors read and approved the manuscript.  
This research was financially supported by the National Key Research and Development Program (2016 YFC1100704, 2016 YFC1102203, 2017 YFC0108505), the Fundamental Research Funds for the Central Universities (No. YWT-19-BJ-203), NSFC Research Grant (11827803, 11421202, 61227902, 31470901), National Key Technology R&D Program (No. 2014 BA11B15), Beijing Municipal Science and Technology Project (No. Z141107002514073), Beijing Municipal Administration of Hospitals Clinical Medicine Development of Special Funding (No. ZYLX201508), the capital health research and development of special funding (No. 2014-1-2091), the 111 Project of China (No. B13003) and Science, Technology and Innovation Commission of Shenzhen Municipality.  
Thanks [PERSON] (Department of Neuroscience, School of Medicine, Johns Hopkins University) for English editing.  
We declare that we have no conflicts of interest to this work.
## 2 Theoretical Basis
### MOPSO-h Algorithm and Applications
#### 2.2.1 Algorithm Principles
\right.. \tag{16}\]  
Given the inherent complexity of missile-trajectory optimization, characterized by its high-dimensional, multi-constraint, and multi-objective nature, the optimization process necessitates the implementation of probabilistic mutation operations during population evolution. These operations play a crucial role in maintaining population diversity, thereby mitigating the risk of premature convergence. This study integrates an adaptive Hybrid Mutation Strategy (HMS) into the standard MOPSO framework, serving as a replacement for conventional mutation operations. The strategy employs uniform mutation during initial iterations to enhance exploration capabilities, while subsequent stages utilize Gaussian mutation for precise optimization. The transition between these phases is dynamically determined based on the monitoring of population hypervolume (HV) trends, as follows:  
\[\mathbf{X}_{n}^{i}=\left\{ \begin{array}{l}\mathbf{X}_{n}^{i}+U\Big{(}\big{(}1-\dot{i} \big{)}(\mathbf{X}_{\max}-\mathbf{X}_{\min})\Big{)},\text{if}\frac{HV_{i}-HV_{i-\Delta} }{HV_{i-\Delta}}>a_{HV}\\ \mathbf{X}_{n}^{i}+\mathcal{N}\Big{(}0,\exp\Big{(}-\dot{i}\Big{)}\sigma_{0}^{2} \Big{)},\text{else}\end{array} \right., \tag{17}\]  
where \(U(\cdot)\) is the uniform distribution function, \(n\) is the adjustment interval of \(HV_{i}\), and \(\mathbf{X}_{\max}\) and \(\mathbf{X}_{\min}\) are the upper and lower boundaries of \(\mathbf{X}\), respectively. When the change in the hypervolume \(HV_{i}\) surpasses the critical value \(a_{HV}\), a uniform variation strategy is implemented. This involves random sampling within interval \(\big{(}1-\dot{i}\big{)}(\mathbf{X}_{\max}-\mathbf{X}_{\min})\) to provide directional guidance for the mutation factor, thereby restricting its variation range and preventing premature algorithm convergence. The parameter \(\Big{(}1-\dot{i}\Big{)}\) exhibits linear decay as the iteration count increases, progressively diminishing its influence on \(\mathbf{X}_{n}^{i}\). In contrast, during the latter stages of iteration, \(\mathbf{X}_{n}^{i}\) approaches the optimal solution and only necessitates fine-tuning, while \(\exp\Big{(}-\dot{i}\Big{)}\sigma_{0}^{2}\), an exponential decay factor, is introduced to induce disturbances around \(\mathbf{X}_{n}^{i}\) until its effect is negligible. The calculation of \(HV_{i}\) refers to the method in reference [34]. Overall, MOPSO-h inherits several implementation techniques from MOPSO, including boundary clipping and constraint repair [35]. Nonetheless, these aspects are not central to the current investigation and, thus, are not elaborated upon in detail.
# An Adaptive Hierarchical Hybrid Multicast Based on Information-Centric Networking
###### Abstract  
Many information-centric services have emerged, such as IPTV and video conferencing. These services put a lot of demands on scalable multicast communication. However, traditional IP multicast has low adoption because of its poor scalability. Therefore, some stateless multicast methods were proposed, which encapsulate the destination's information into the packet header without requiring routers to maintain the multicast forwarding state. However, stateless multicast also faces some problems, such as ingress router overload, high forwarding overhead, packet redundancy, etc. In addition, most multicast methods cannot optimize the multicast tree because the multicast flow is simply forwarded along the shortest path tree from the source to receivers. This paper proposes an Adaptive Hierarchical Hybrid Multicast (AHHM) based on Information-Centric Networking. To balance the forwarding states and forwarding overhead, AHHM is designed as a two-layer structure, in which the upper layer establishes a stateful main tree and the lower layer establishes several stateless sub trees. The router on the main tree is defined as the multicast join node (MJN), and AHHM uses the Name Resolution System to maintain the mapping between each multicast group name and corresponding MJNs. To optimize the multicast transmission path, we designed the minimum cost selection strategy for users to select the appropriate MJN to join. Simulation results show that compared with Source-Specific Multicast (SSM) and Bit Index Explicit Replication (BIER), AHHM can not only reduce the multicast forwarding states but also reduce the control overhead and link load.  
multicast; scalability; icr; forwarding states; link load +
Footnote †: journal: _electronics_
## 5 Conclusions  
In order to improve the communication performance of the FSO system, this paper proposed a multi-hop parallel hybrid FSO/RF cooperation transmission scheme. By analyzing the end-to-end instantaneous SNR of the FSO-only direct link, the hybrid FSO/RF direct link, and the multi-hop parallel hybrid FSO/RF system, new mathematical expressions of the ABER and outage probability of them with CBPSK and DBPSK subcarrier modulation were derived. Through system simulation, the effects of turbulence intensity, pointing errors, modulation mode, and the RF fading parameter on the FSO-only direct link, the hybrid FSO/RF direct link, and the multi-hop parallel hybrid FSO/RF system were analyzed.  
According to the research and analysis of this paper, we obtained some important conclusions. Affected by atmospheric turbulence and pointing errors, the transmission distance and communication performance of the multi-hop parallel hybrid FSO/RF system were the best, followed by the hybrid FSO/RF direct link, and the performance of the FSO-only direct link was the worst. For the multi-hop parallel hybrid FSO/RF system, only increasing the number of hops increased the transmission distance; however, this reduced the communication performance of the system.  
By increasing the number of transmission paths, the multi-hop parallel hybrid system significantly improved the ABER and outage probability performance. The RF fading parameter \(m^{RF}\) had a great impact on the performance of the hybrid FSO/RF direct link, and the communication performance of the hybrid direct link was significantly improved when \(m^{RF}\) increased. The performance of the hybrid direct link with coherent modulation was better than that with differential modulation.  
Conceptualization, Y.W. and D.K.; methodology, Y.W. and G.L.; software, Y.W. and J.G.; validation, Y.W. and J.C.; formal analysis, Y.W.; writing--original draft preparation, Y.W. and D.K.; writing--review and editing, Y.W. and D.K.; supervision, D.K. All authors have read and agreed to the published version of the manuscript.  
This research was funded by National Science Foundation of China (No. U2141255) and National Science Foundation of China (No.62001333).  
Not applicable.  
Figure 6: Relationship between outage probability and the normalized SNR of the multi-hop parallel hybrid FSO/RF system, the hybrid FSO/RF direct link, and the FSO-only direct link under different relay-assisted structures and pointing errors.
## 2 Enhancing Food Production through RS Applications in Agriculture  
Monitoring agricultural activities through traditional approaches can be challenging because of the following. Firstly, usually agricultural regions are large, and their effective monitoring requires repeated coverage [31]. Secondly, yield prediction is based commonly on monitoring the growth phases of crops and information obtained via traditional approaches is often limited [36]. In addition, challenges with geographic access to many areas in ASA regions due to political instabilities mean that RS data can be used as a potential source to complement traditional approaches for collecting agricultural data. There are many RS applications in agriculture. We selected and explored a few key applications to keep the paper concise. In particular, this paper focuses on the three main RS applications in Middle Eastern and African ASA countries including identifying and estimating crop area, monitoring agricultural status, and modelling and forecasting future crop yield. These  
Figure 1: Global distribution of arid and semi-arid (ASA) regions [38]. It is estimated that arid regions cover around 28 million km\({}^{2}\) while semi-arid regions cover around 46 million km\({}^{2}\).  
RS applications are critical in these regions since the smallholder farming system is complex and agricultural management is heterogeneous [39]. In addition, due to their fragile climatic conditions and often political instabilities, these areas are prone to many crises which can induce regional food insecurity [29]. Despite these challenges, several regional characteristics can influence the RS proxies that are used as a base for these applications which will be discussed in the following sections. In such conditions, and due to lack of data and resources, RS can provide remote and cost-effective solutions and improve regional food security [40]. Table 1 provides a summary of the role of remote sensing applications for increasing agricultural productivity and food security.
## 4 Experiments
### CEC 2019 Benchmark  
This study employs the CEC2019 test suite to evaluate the performance of optimization bio-inspired algorithms. It is important to note that maximization and minimization problems can be converted into one another; therefore, all test functions are defined as minimization problems: \(\text{Min}\,f(x)\), where \(x\) represents the D-dimensional space variables, and \(f(x)\) denotes the objective function. The CEC2019 function set serves as an effective benchmark for testing the performance of metaheuristic algorithms. In CEC2019, the functions F1-F3 exhibit different dimensions and ranges, while the F4 function is formulated as a 10-dimensional minimization challenge. Given that many of the CEC2019 test functions are multimodal, they present substantial challenges.  
As shown in Table 3, the benchmark test functions vary in dimension and search range, providing a robust evaluation environment for the proposed algorithm.  
Each algorithm is independently evaluated on the CEC 2019 benchmark suite to assess its performance across various test cases. The algorithms are evaluated by ranking the average statistical outcomes of the benchmark set to identify their top performances or optimization abilities. Additionally, the robustness of the algorithms is evaluated by examining the standard deviation (SD) results for each benchmark set.  
After evaluating the effectiveness of the model parameters, the improved GWO method was employed to optimize the model parameters. The parameters in the LSTM were used as the position vectors of the grey wolves, and the MAPE evaluation metric of model training was used as the fitness function. Upon executing the IGWO technique, optimal network model parameters were obtained. Figure 7 shows the convergence behavior of the GWO and MTGWO algorithms on the four benchmark test functions (CEC-01 to CEC-04).  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Func.** & **Descriptions** & **Dim** & **Range** & \(f_{min}\) \\ \hline CEC-01 & \begin{tabular}{c} Storm’s Chebyshev Polynomial \\ Fitting Problem \\ \end{tabular} & 9 & \([-8192,\,8192]\) & 1 \\ CEC-02 & \begin{tabular}{c} Inverse Hilbert Matrix Problem \\ \end{tabular} & 16 & \begin{tabular}{c} \([-16,\,384,\) \\ \(16,\,384]\) \\ \end{tabular} & 1 \\ CEC-03 & \
\begin{tabular}{c} Lennard-Jones Minimum Energy \\ Cluster \\ \end{tabular} & 18 & \([-4,\,4]\) & 1 \\ CEC-04 &
\begin{tabular}{c} Rastrigin’s Function \\ \end{tabular} & 10 & \([-100,\,100]\) & 1 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Lists the four common test functions used in this study.
Our team is building another six radar stations within the PRE. Given that most in situ measurements are mainly deployed within the PRE, the HF radar data on the continental shelf cannot be validated directly against in situ data. In this study, a regional high-resolution ocean model covering the PRE and its adjacent seas was first established and validated with the in situ measurements in the PRE, and the HF radar-derived tidal currents were then examined through comparison with the model results. Furthermore, a set of sensitivity experiments were conducted to explain the role of physical factors in affecting the tidal currents. This study serves as a first step toward the full deployment of the entire radar network, aiming to assess the currently available radar measurements, the model's development, and in situ observations. We note that both radar and model are not perfect, but this work will provide us and readers with very useful information to proceed with the construction and improvement of the entire PRE radar network.
## 1 Introduction
### Contributions  
The following is a summary of our work's main contributions:  
1. The traditional identity systems have security vulnerability and depend on trust in third-party authority. Those systems may cause a lack of autonomy, single-point failure, and privacy leaks when we apply them to the cloud CDM. Self-sovereign identity (SSI) allows researchers to provide their identity information with the confidential token controlled by themselves. To design the cloud CDM, we apply SSI as an identity management model that offers a way to handle the programs caused by a third-party authority.
2. The main purpose of the cloud CDM is to collaborate with hospitals and research institutes in order to share Electronic Medical Records (EMR) with diverse formats. EMRs contain confidential private information about patients. Secure and reliable identity management is one of the basic requirements for building an e-health service in the cloud CDM participating in multiple institutes. To build the cloud CDM, the enhanced decentralized identifier and verifiable credential approach prevents disclosing who owns the privacy attribute in the user's wallet while defining it. This proposed model acknowledges the de-linkability between the users and their identity.
3. In this proposed model, a user must demonstrate ownership of the identifier in order to access the service provided by the service provider. This is often done by making a transfer from the wallet associated with the user's blockchain account. The service provider can then retrieve the entire identification.
# A Survey of Vehicle to Everything (V2X) Testing
## 5 V2X Testing Methods
### Penetration Testing
360, Visual Threat, Rapid7 and other companies have formed security teams to provide penetration testing services for communication protocols, mobile terminal APP, Cloud API, firewalls and etc.
# Ultra-Wideband Antenna Design for 5G NR Using the Bezier Search Differential Evolution Algorithm
## 1 Introduction
All in all, the aforementioned characteristics of the optimal antenna, in addition to its efficiency, impedance response (around \(50+0j\) Ohm), \(S_{11}\) response (below \(-10\) dB), and omnidirectionality, across the frequency band, make it a sufficient design for a variety of applications, including most rectenna scenarios, as it is capable of meeting all the conditions to efficiently harvest energy from all the vastly used telecommunication technologies. The contribution of this work can be summarized as follows:  
* We design a novel ultra-wide band antenna for RF energy harvesting applications with more than a 2 GHz bandwidth. We introduce a recent optimization algorithm (BeSD) for antenna design. To the best of our knowledge, this is the first time BeSD has been applied to an optimization problem in electromagnetics. In the remaining sections, this work is detailed as follows. Section 2 describes the optimization process, focusing on the BeSD algorithm approach, as well as on the implementation of the CST-Matlab API. In Section 3 the initial and optimal antenna designs are compared, in terms of factors like the \(S_{11}\) response, the Z response, efficiency, complexity, omnidirectionality, etc. Lastly, Section 4 concludes the research by summarizing the results and making closing arguments about future efforts to optimize antenna structures.