esa-sceva/satcom-chunk-collection huggingface dataset:
# Model-Free Robotic Architecture with Task-Multiplexer and Discrete-Time Adaptive Control
## 3 Identification of an Equivalent Model
\begin{array}{rcl}\tilde{\beta}_{t}(k+1)&=&\tilde{\beta}_{t}(k)-\eta_{h}(k) \vartheta_{t}(k)[\tilde{\beta}_{t}^{T}(k)\vartheta_{t}(k)+\varepsilon_{h}(k) ],\\ &=&[I-\eta_{h}(k)\vartheta_{t}(k)\tilde{\sigma}_{t}^{T}(k)]\tilde{\beta}_{t}(k )-\eta_{h}(k)\varepsilon_{h}(k)\vartheta_{t}(k),\\ &\leq&[1-\eta_{h}(k)||\vartheta_{t}(k)||^{2}]\tilde{\beta}_{t}(k)+\eta_{h}(k) \varepsilon_{H}\vartheta_{t}(k).\end{array}  \tag{16}\]  
The second term of the right-hand side of (16) is always bounded. Thus, the convergence of the sequence \(\tilde{\beta}_{t}(k)\) requires  
\[-1<1-\eta_{h}(k)||\vartheta_{t}(k)||^{2}<1. \tag{17}\]  
By using the learning rate \(\eta_{h}(k)\) from (11), the condition (17) always holds. The convergence proof of internal signals is completed. Next, the convergence proof of \(\hat{e}(k)\) is conducted. Let's define the change of \(\hat{e}(k)\) as  
\[\Delta\hat{e}(k)=\hat{e}(k+1)-\hat{e}(k). \tag{18}\]  
The change in (18) can be approximated by  
\[\Delta\hat{e}(k)\approx\Big{[}\frac{\partial\hat{e}(k+1)}{\partial\beta_{t}(k )}\Big{]}^{T}\Delta\beta_{t}(k). \tag{19}\]  
According to (12), we have  
\[\frac{\partial\hat{e}(k+1)}{\partial\beta_{t}(k)}=\eta_{h}(k)\vartheta_{t}(k), \tag{20}\]  
and  
\[\Delta\beta_{t}(k)=\eta_{h}(k)\vartheta_{t}(k))\hat{e}(k+1). \tag{21}\]  
Substitution of (20) and (21) into (19) leads to  
\[\Delta\hat{e}(k)\doteq\eta_{h}^{2}(k)||\vartheta_{t}(k)||^{2}\hat{e}(k+1). \tag{22}\]  
By setting (18) equal to (22), we have  
\[\hat{e}(k+1)-\hat{e}(k)=\eta_{h}^{2}(k)||\vartheta_{t}(k)||^{2}\hat{e}(k+1), \tag{23}\]  
and  
\[\hat{e}(k+1)=\frac{1}{1-\eta_{h}^{2}(k)||\vartheta_{t}(k)||^{2}}\hat{e}(k). \tag{24}\]  
The convergence of the sequence \(\hat{e}(k)\) in (24) can be guaranteed when  
\[-1<\frac{1}{1-\eta_{h}^{2}(k)||\vartheta_{t}(k)||^{2}}<1. \tag{25}\]  
By using the learning rate in (11), the condition in (25) always holds. The convergence proof of the approximation error is completed. Utilizing the equivalent model given by (6)-(8), the controller will be established by another MiFREN in the next section.
# Quality of Service Based NOMA Group D2D Communications
## 1 Introduction
### Related Work and Motivation
This assumption may not always hold, particularly in the scenario of NOMA based D2D communications because DRs are clustered around DTs and are located in proximity of each other and hence DRs may have very similar channel conditions. In the light of the abovementioned discussion, very little attention was paid to investigate NOMA group D2D communications. Hence, the aforementioned gaps and shortcomings motivated us to investigate and analyse the performance of NOMA based group D2D communications under interference limited scenarios. In order to capture the key features of D2D communications, i.e., device clustering and spatial separation, the DTs are considered to be randomly distributed over \(\mathbb{R}^{2}\) according to Gauss-Poisson process (GPP), while the DRs are assumed to be randomly clustered around DTs. The reason for choosing GPP is that it is a relatively simpler cluster point process that maintains good trade-off between modeling accuracy and analytical tractability. Therefore, in the context of D2D communications, GPP provides more realistic modeling approach against PPP case by capturing the clustering behavior of D2D devices [21]. Furthermore, the current approach to order users in NOMA group D2D communications is based on the channel gains of the DRs. This ordering approach may not be suitable to D2D communication scenario under which the DRs in the same group are clustered around a common DT and are located in proximity of each other. Hence, the channel conditions of the DRs located in the same D2D group would be very similar. Consequently, this ordering strategy may result in very similar power allocation, which could limit the gains of applying NOMA to D2D communications [7]. In the context of NOMA, there are few works that use quality of service (QoS) based ordering [22; 23; 24]. They mainly focused on cellular networks and are limited to the two-user case only. In this paper, we propose and analyse QoS based NOMA (Q-NOMA) group D2D communications and make an attempt to fill the aforementioned gaps in literature. To the best of our knowledge, it is the first time that Q-NOMA is proposed and analysed to realize group D2D communications under interference limited scenario.
## 5 Results
Using a gain of 50 dB provides an excessive increase in frequency (Figure 8 panel C5). Comparing different distributions of Q values for chosen gain 40 db (Figure 9 panels C2-C5), we can conclude that the variant with an estimated variable Q distribution (panel C4) makes the dominant signal frequency increment by 9 Hz (Figure 10), practically to the level of the section with VSP (Figure 9 panel B). The significant increase in vertical resolution makes the sequence of reflections on the PreSTM section after IQF similar to those occurring on the VSP corridor sum. This is seen in the key reflection marked in Figure 8 with point X, which on the original PreSTM section is characterized by a single, large amplitude (upper panel Figure 11), while on the post-IQF and VSP data, it clearly splits into two reflections (lower panel Figure 11), thus signaling the presence of a thin overlap at this location, as confirmed by the lithological profile derived from the well-log data. In the higher frequency range, the IQF procedure  
Figure 9: The results of the IQF procedure tested in different distributions of Q values. Amplitude gain limit was chosen as 40 db. Left panel shows well log data with lithological interpretation, middle section is the processed zero offset VSP. On the right: seismic panels with Q depth distributions. Point X shows example of the vertical resolution increase resulting in the separation in whole or in part of some reflections and a noticeably better fit of the seismic image to the attached VSP result. The red box in section C indicates which Q distribution gives the optimal increase in the vertical resolution in terms of matching to the VSP data. By yellow color lines marked Well Tracks, by blue and orange color lines marked Synthetic Seismograms. improves the link of the synthetic seismogram to the seismic record (marked section on Figure 9). Even subtle seismic reflections of small amplitudes created after IQF are reflected in the synthetic seismogram (lower panel Figure 11). Figure 11: _Cont._  
Figure 10: Seismic section power spectra after PreSTM and after IQF for G = 30 and 40 dB (IQF for Q values presented at (Figure 7) with the Q value of 25 at the near surface). Broadening the frequency spectrum of the signal towards higher frequencies increases the vertical resolution of seismic data, often making it easier for interpreters to separate thin layers not imaged by classical approaches due to signal interference.
# Mapping irrigated Areas Using Sentinel-1 Time Series in Catalonia, Spain
## 5 Discussion
### Comparison of \(\sigma^{\circ}\) SAR Backscattering at Plot and Grid Scale  
Using S1 data only, the analysis of the \(\sigma^{\circ}\) SAR temporal series showed that an irrigated plot encounters a frequent change of the \(\sigma^{\circ}\) SAR backscattering coefficient due to the artificial application of water. This change in the \(\sigma^{\circ}\) should be differentiated from the change in \(\sigma^{\circ}\) due to the rainfall events. Thus, the ambiguity between rainfall events and irrigation event was the most challenging point using S1 data. To overcome this uncertainty, the \(\sigma^{\circ}\) SAR backscattering coefficient at plot scale was compared to that obtained at grid scale (10 km \(\times\) 10 km). The assumption says that if the mean S1 signal within 10 km \(\times\) 10 km grid cell, obtained from the bare soil plots with low vegetation cover, increases between two consecutive dates then a rainfall event took place. On the other hand, if \(\sigma^{\circ}\) value increases at plot scale with stability or decrease of \(\sigma^{\circ}\) SAR backscattering coefficient obtained at grid scale then an irrigation event most probably took place. This dependency was clearly shown in Figure 6 for the irrigated and non-irrigated plots. Therefore, the difference between \(\sigma^{\circ}\) SAR at plot and grid scales helps remove the ambiguity between rainfall and irrigation events.
# Advanced Metal Matrix Nanocomposites
## 6 Mechanical Properties
It has been observed that during high temperature sintering, carbonaceous materials react with matrix and forms carbides, such as aluminum carbide in the case of Al matrix, which reduces the mechanical properties of composites [170; 171]. To overcome this concern a rapid sintering process, such as laser sintering, has been used that has improved the mechanical properties of the composites [170; 172]. These studies suggest that the PM route provides an alternative to the casting process, especially for the production of small components because the PM route generates finished products. \begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Matrix**} & \multirow{2}{*}{**Reinforcement-Content**} & **\% Improvement in Mechanical/Tribological** & \multirow{2}{*}{**Reference**} \\  & & **Properties with Respect to Matrix Material** & \\ \hline Aluminum & Gr = 1.5 wt\% & TS = 63\% & [173] \\ Al6061 & Gr = 1 wt\% & Flexure strength = 15\% & [174] \\ Aluminum & Gr = 0.5 wt\% & TS = 16\% & [175] \\ AA6061 & Gr = 10 vol\% & E = \(-\)35\%, Hardness (H) = \(-\)13\%, COF = \(-\)72\%. & [176] \\ AA2124 & Gr = 3 wt\% & Wear rate = \(-\)47\% & [174] \\ Copper & Gr = 1 wt\% & TS = 12\% & [177] \\ Ti & Gr = 5 wt\% & H = 200\% & [172] \\ Aluminum & CNT = 5 wt\% & TS = 100\% & [178] \\ Aluminum & CNT-1 wt\% & TS increased four times and no change in elongation & [179] \\ Aluminum & CNT = 5 wt\% & Hardness = 28\%, COF = \(-\)100\% & [180] \\ Aluminum & CNT = 0.4 wt\% & TS = 30\%, Elongation reduced from 35 to 1\%. & [171] \\ Copper & CNT = 16 vol\% & H = 94\%, COF = \(-\)100\% & [181] \\ Ni & CNT = 10 vol\% & COF = \(-\)100\% & [182] \\ Aluminum & SiC = 10 wt\% & Compressive strength = 71\% & [183] \\ \hline \hline \end{tabular}  
Negative sign indicates reduction in properties.  
\end{table} 
Table 6: Mechanical and tribological properties of MMNCs produced by the powder metallurgy route. Figure 22: Minimum creep rate vs. applied stress for Mg alloy (Elektron21) and Mg alloy-AlN composite at 240 \({}^{\circ}\)C [128].
## 8 Conclusions  
In conclusion, the results obtained in this study are consistent with previous research focusing on the adjustment of propagation models, such as the SUI, to improve accuracy in complex environments across various distances, frequencies, and technologies. When comparing the signal levels of the hotspot and the Wi-Fi repeater (Raspberry Pi 3), it was observed that the adjusted model for the hotspot exceeded the field-measured levels, especially beyond 60 m. However, at a power level of \(-70\) dBm, the data began to better match the adjusted model. Additionally, the discrepancies between the heatmaps shown in Figures 9 and 11 can be explained by the higher transmission power of the hotspot compared to the repeater, resulting in different signal levels. Regarding reception, the signal levels of the hotspot were low at distances close to the transmitter, which led to new data collection with the Wi-Fi repeater. It is noteworthy that when analyzing the curves of the two models adjusted by linear and logarithmic regression in Figure 15, it was observed that the logarithmic model fits the data better, especially in the range of \(-40\) dBm to \(-98\) dBm. This model provided better prediction of signal loss, with a path loss exponent (\(\gamma^{*}\)10) of 8.96, demonstrating an adequate fitting process. These results support the adjustment of propagation models like the SUI and show how logarithmic models improve prediction accuracy, particularly at short distances (0 to 100 m).  
The use of mathematical tools such as MATLAB and reference models is crucial for optimizing propagation models. The logarithmic adjustment proposed, presented through Equation (22), improves prediction accuracy and optimizes network planning in local areas, providing the Universidad de las Americas with a valuable tool for generating heatmaps in parishes with conditions similar to those of Checa. This suggests that future research could further refine these models to optimize resources and enhance performance in community Wi-Fi networks in areas with similar characteristics.  
Conceptualization, I.S. and F.V.; methodology, I.S. and F.V.; software, I.S. and F.V.; validation, P.P.J. and I.S.; formal analysis, I.S. and F.V.; investigation, I.S. and F.V.; resources, I.S. and F.V.; data curation, I.S., F.V. and A.D.F.; writing--original draft preparation, I.S. and F.V.; writing--review and editing, P.P.J. and A.D.F.; supervision, P.P.J. and I.S.; project administration, P.P.J. and I.S.; funding acquisition, P.P.J. and I.S. All authors have read and agreed to the published version of the manuscript.  
This research was funded by ANID/FONDECYT Iniciacion No. 11240799, ANID FONDECYT Regular 1211132, ANID/FONDECYT Iniciacion No. 11230129, SENESCYT \"Convocatoria abierta 2014-primera fase, Acta CIBAE-023-2014\"; and UDLA Telecommunications Engineering Degree FICA, UDLA.  
Not applicable.  
Dataset available on request from the authors.  
The authors declare no conflicts of interest.
# Mechanical and Microstructural Studies of High Performance Concrete with Condensed Silica Fume
## 1 Introduction
For some of them, the CSF replacement is approximately 15% [11], while for others, the increase in mechanical characteristics can be reached from 30% to 40% of the CSF [41]. [PERSON] et al. [4] indicated that 10% CSF is considered ideal. Nevertheless, the cement portion can be substituted by CSF, making at least equivalent performance to HPC, reducing the CO\({}_{2}\) footprint. In recent years, researchers have considered the influence of CSF on HPC performance, and their results indicate that the mechanical assets and durability of HPC are greatly improved when CSF is added. Despite the large amount of data on HPC, the current knowledge on the HPC fracture properties development with CSF content, which is beneficial for the safety of concrete structures, is still insufficient. This topic has been discussed in investigations by [PERSON] et al. [14], [PERSON] at al. [15], as well as [PERSON] and [PERSON] [35]. Over the past several decades, various types of fibers have been applied to increase the flexural toughness as well as crack resistance of HPC [42; 43; 44; 45]. Fracture characteristics are very essential for durability and safety of HPC. Though, little information is currently available regarding the effect of SiO\({}_{2}\) microparticles on HPC fracture properties. This article is an extended version of the conference paper \"Influence of silica fume on mechanical and fracture properties of high performance concrete\" published in Procedia Structural Integrity as a part of the Special Issue of the 3 rd International Conference on Structural Integrity (ICSI 2019) [23]. In this work, the effects of CSF on the compressive strength and fracture characteristics of HPC with CSF addition from 5% to 25% were investigated. The water to binder ratio (W/B) was 0.25. HPC samples were also examined to determine elastic modulus and splitting tensile strength. The results are given at 28 days after water curing at 20 \({}^{\circ}\)C. In order to observe the effect of CSF on fracture characteristics of HPC, the mid-span deflection, stress intensity factor, elastic-plastic failure parameter, fracture energy, crack mouth opening displacement (CMOD), crack tip opening displacement (CTOD), and characteristic length of HPC notched beam specimens containing CSF were determined. Moreover, research was conducted to study the impact of CSF on the macro- and microstructural development of HPC.
# On-Demand Scheduling of Command and Responses for Low-Power Multihop Wireless Networks +
## 4 SCoRe Design  
This section presents the design of SCoRe based on the following system requirements for joint packet scheduling in multihop wireless networks. SCoRe targets IoT application scenarios in which commands are disseminated into the network from the root (e.g., server, gateway, or access point), and their corresponding responses need to be collected reliably with low latency.  
Figure 1: Grid topology for the preliminary simulation and the result.  
Adaptation to network topology: Routing topology in wireless networks are rarely static, and any inconsistency between route and schedule may result in significant performance loss. Therefore, resource scheduling should dynamically adapt to number of devices, physical relocation, and routing topology changes possibly due to link quality variations. Little control/memory overhead: Low-power embedded systems with resource constrained devices are typically intolerant of extra packet overhead for energy and bandwidth reasons. Furthermore, multihop routing protocols may take either the storing mode or non-storing mode [24; 42] approach depending on the memory constraints for routing tables. Thus, scheduling protocol should generate minimal packet overhead, information exchange should be done locally without a global routing table, and should support both storing and non-storing mode of operation. Furthermore, global time synchronization in a multihop network is a complex task [43; 44] and should be avoided if possible.
* Efficient resource assignment over multihop: Because we target multihop, the number of total transmissions required to reach the root (even for same number of devices) depends on the location of each node in the topology. Assigning a dedicated, exclusive transmission slot within the whole network may be a must in a 1-hop TDMA system for fair channel access, but would be too naive in multihop networks. Nodes that do not interfere with each other should be able to transmit concurrently (spatial re-use) for improved latency and bandwidth.  
SCoRe is designed to satisfy these requirements while disseminating commands and collecting responses reliably and promptly. Each SCoRe node calculates \"the number of desired timeslots for both command dissemination and response collection\" (hereinafter referred to as \(N_{\text{dslot}}\)) it needs based on its routing information. Each node also calculates its subtree-aggregate \(N_{\text{dslot}}\) (including those needed for its subtree), and reports that to its routing parent. Then, the sum of these \(N_{\text{dslot}}\) is piggybacked in regular routing messages [23; 24], and will eventually reach the root. When a command needs to be disseminated, SCoRe's root debriefs these \(N_{\text{dslot}}\) from network nodes, and assigns required aggregate timeslot chunks to (and only to) each of its 1-hop children. Then, upon reception of a new command, each node uses assigned slots for itself and its subtree nodes recursively. The details of SCoRe are explained in following subsections.
# Surface Correlation-Based Fingerprinting Method Using LTE Signal for Localization in Urban Canyon
## 4 Experiments and Results  
### Test Environment  
To verify the proposed fingerprinting method, we performed tests in Barcelona's old districts with a common commercial smartphone as shown in Figure 12. Before the test, we constructed a fingerprinting database consisting of 20 links and 13 nodes through several surveys of the test area.  
Figure 11: The localization of the Surface Correlation (SC) method in case of a turn back event: (**a**) Links for the generation of a reference trajectory; (**b**) Test route for a turn back event; (**c**) SSD; (**d**) Localization error by comparison with GPS.  
As shown in Figure 13a, four BSs are available on average on each link. Over 10 BSs were available in a square or a relatively wide alley, but only one BS was available in narrow alleys. In addition, measured RSS detected as very low in most RPs, as shown in Figure 13b. As shown in Figure 14a and b, tests were performed in two scenarios as follows: (1) From an open space into a narrow alley; (2) From the narrow alley to an alley. In order to analyze the performance in each scenario, localization results from PDR were corrected by applying a map-matching algorithm and it was considered as a true location. Collected data from the smartphone were as follows:  
* Inertial Measurement Unit (IMU): 40 Hz
* PCI & RSS of LTE: 0.5 Hz
* GNSS: 1 Hz  
Figure 12: Test Site.  
Figure 13: The condition of the Long-Term Evolution (LTE) environment in the test site: (**a**) The number of available BSs at each link; (**b**) The maximum RSS at each RP.
# Confidential Smart Contracts and Blockchain to Implement a Watermarking Protocol
## 7 Security Analysis
### Analysis
Following the \"buyer-friendly\" approach, \(\mathcal{B}\) participates in the protocol without generating tokens or security information except for \(B_{id}\), which qualifies its identity. In fact, \(B_{id}\) is assumed to be valid since the problems resulting from false identities are not considered in this analysis. Therefore, the tokens that \(\mathcal{B}\) exchanges in messages are generated by other entities and can only be confirmed by \(\mathcal{B}\), under penalty of interrupting the purchase transaction as a result of the checks performed at the end of the first or second phase of execution of the smart contract. Consequently, in this hypothesis, no content is released by \(\mathcal{CP}\) in accordance with the provisions of Section 7. Suppose that \(\mathcal{CP}\) is corrupt. In this case, \(\mathcal{CP}\), which is responsible for inserting the watermark into \(X\), can maliciously generate or attempt to alter the tokens it is responsible for, such as \(X_{d}\) and \(T_{X}\), or the tokens to be used to protect \(X\). However, the checks performed by the two phases of execution of the smart contract, as reported above, force \(\mathcal{CP}\) to behave as follows:  
* \(\mathcal{CP}\) cannot reuse tokens already used in previous transactions;
* \(\mathcal{CP}\) cannot modify or change the part of the watermark generated during the first phase of the smart contract execution, nor reuse watermarks used to protect other content. This is because all tokens validly used in previous purchase transactions are published on \(\mathcal{BC}\). In detail, \(X_{d}\) and \(T_{X}\) are published in clear text, and any previous duplication can be directly verified by the smart contract. As regards tokens for which only the digest is published, it is necessary to observe that they are generated by the smart contract during the first execution phase, are published in the form of an encrypted state on the blockchain, and must be confirmed by \(\mathcal{B}\) and \(\mathcal{CP}\) during the second execution phase of the smart contract. Therefore, any watermark generated or reused independently by \(\mathcal{CP}\) to protect \(X\) that is different from the one generated by the smart contract during the first execution phase can never be inserted in the purchase license downstream of the second execution phase of the smart contract. Such a condition can only lead to the generation of protected content \(\hat{X}\) that cannot be validly linked to any buyer since no valid purchase license can be associated with it. This result would end up damaging \(\mathcal{CP}\) itself, which would release incorrectly protected content. In essence, the immutability of the smart contract code, its secure execution in TEE, and the exchange and publication of tokens and security information always in encrypted form on blockchain guarantee the security of the proposed protocol both with respect to corrupt entities and to \"honest-but-curious\" ones.