esa-sceva/satcom-chunk-collection huggingface dataset:
# An Upgraded Version of the Binary Search Space-Structured VQ Search Algorithm for AMR-WB Codec
###### Abstract  
Adaptive multi-rate wideband (AMR-WB) speech codecs have been widely used for high speech quality in modern mobile communication systems, e.g., handheld mobile devices. Nevertheless, a major handicap is that a remarkable computational load is required in the vector quantization (VQ) of immittance spectral frequency (ISF) coefficients of an AMR-WB coding. In view of this, a two-stage search algorithm is presented in this paper as an efficient way to reduce the computational complexity of ISF quantization in AMR-WB coding. At stage 1, an input vector is assigned to a search subspace in an efficient manner using the binary search space-structured VQ (BSS-VQ) algorithm, and a codebook search is performed over the subspace at stage 2 using the iterative triangular inequality elimination (ITIE) approach. Through the use of the codeword rejection mechanisms equipped in both stages, the computational load can be remarkably reduced. As compared with the original version of the BSS-VQ algorithm, the upgraded version provides a computational load reduction of up to 51%. Furthermore, this work is expected to satisfy the energy saving requirement when implemented on an AMR-WB codec of mobile devices.  
speech codec; vector quantization (VQ); codebook search; immittance spectral frequency (ISF) +
Footnote †: journal:  
Article An Upgraded Version of the Binary Search Space-Structured VQ Search Algorithm for AMR-WB Codec
## 2 Materials and Methods
### Gain
#### 2.5.1 Analysis of Signal Attribute (Instantaneous Phase)  
Some forms of advanced field data processing were also performed to enhance the subtle inherent information within the propagating media. The GPR signal attributes were calculated using mathematical functions in the algorithms of the software package, which operate on the individual traces and, thus, allow for the estimation of the instantaneous parameters such as the frequency, amplitude, and phase. It is obtained by the Hilbert transform, which allows the filtering function to pass through the amplitude of the spectral components without any interruption but changes the spectral parts' phases by ninety degrees [30]. According to [PERSON] [31; 32] and [PERSON] [33], if geophysical signals such as GPR and seismic traces can be equated as \(s(t)\), and their envelope and phase written as \(a(t)\) and \(\vartheta(t)\), respectively, the following is true.  
\[s(t)=a(t)\cdot\cos(\vartheta(t)) \tag{3}\]  
Similarly, the quadrature (imaginary) trace of the same signal may be written as follows:  
\[s^{*}(t)=a(t)\cdot\sin(\vartheta(t)) \tag{4}\]  
then, the complex (analytical) trace \(z(t)\) may be denoted by the following equation.  
\[z(t)=s(t)+i\cdot s^{*}(t)=a(t)\cdot e^{i\cdot\vartheta(t)} \tag{5}\]  
From the computation of the complex trace, which has the components of real and imaginary, the instantaneous amplitude \(a(t)\) and the phase \(\vartheta(t)\) can be obtained from Equations (6) and (7), respectively.  
\[a(t)=[s(t)^{2}+s^{*}(t)^{2}]^{1/2} \tag{6}\]  
\[\partial(t)=\tan^{-1}[\frac{s^{*}(t)}{s(t)}] \tag{7}\]  
The different attributes allow us access to deeper information about the interactions of the propagated EM energy and the media. Instantaneous frequency helps to identify separate reflections that arrive at the same time. The instantaneous phase, emphasized in this report, allows for the delineation of thin layers and trace continuity of reflection [18]. Thus, it could be useful for revealing the zone of alteration in the soil horizons.  
It is worth noting that the implementation of the described processing routines may vary from application programs, and yet the purpose of using them is always the same.
# A Comprehensive Review of Mechanisms, Predictive Techniques, and Control Strategies of Rockburst
## 7 Conclusions
Energy-absorbing rockbolts can be used for rock support, either installed internally within the rock mass or externally for surface support. Further research and exploration into the following topics will be needed in the future:  
* The quest to accurately predict rockbursts is ongoing, with many techniques developed to determine rockburst intensity and location. However, the elusive challengeremains--predicting the occurrence time of rockburst. Further investigation and exploration are needed, and the microseismic monitoring method may hold the key to unraveling the regularities of rock rupture signals over time. * Despite numerous efforts to predict and prevent rockbursts, the prediction accuracy remains wanting and rockburst accidents persist. The complexity of anisotropic and inhomogeneous rock masses and the unpredictable external environment call for more focused research into rockburst prediction and prevention methods in uncertain situations. * Current rockburst stress and energy methods rely heavily on curve interpolation, lacking adequate validation from actual data. To establish more accurate predictions, a comprehensive database of rockburst events from all sources should be created, and empirical methods should be applied for verification against real-life rockburst occurrences. * Experiments and numerical models, such as virtual hybrid simulations, hold great potential to enhance our understanding of rockbursts. The need of the hour is to develop a multi-parameter evaluation model that is effective, reliable, robust, and efficient to make accurate predictions and provide effective mitigation strategies. If these challenges are tackled, the practical use of these techniques for rockburst prediction will be streamlined and bring numerous benefits. Conceptualization, S.G. and S.Q. ; methodology, M.F.W. ; investigation, S.G. and S.Q. ; writing--original draft preparation, M.F.W. ; writing--review and editing, S.G.; supervision, S.G. and S.Q. All authors have read and agreed to the published version of the manuscript. This work was funded by the Second Tibetan Plateau Scientific Expedition and Research Program (STEP) under Grant No. 2019 QZKK0904, the National Natural Science Foundation of China under Grants Nos. 42077266, 41825018, 42141009, and 42090051, and the Youth Innovation Promotion Association of the Chinese Academy of Sciences under grant No. 2022062. A special acknowledgement should also be expressed to the China-Pakistan Joint Research Centre on Earth Sciences that supported the implementation of this study. Not applicable. Data Availability Statement: Data are contained within the article. The authors declare no conflict of interest.
# Vehicle Collision Prediction under Reduced Visibility Conditions
###### Abstract  
Rear-end collisions often cause serious traffic accidents. Conventionally, in intelligent transportation systems (ITS), radar collision warning methods are highly accurate in determining the inter-vehicle distance via detecting the rear-end of a vehicle; however, in poor weather conditions such as fog, rain, or snow, the accuracy is significantly affected. In recent years, the advent of Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) communication systems has introduced new methods for solving the rear-end collision problem. Nevertheless, there is still much left for improvement. For instance, weather conditions have an impact on human-related factors such as response time. To address the issue of collision detection under low visibility conditions, we propose a Visibility-based Collision Warning System (ViCoWS) design that includes four models for prediction horizon estimation, velocity prediction, headway distance prediction, and rear-end collision warning. Based on the history of velocity data, future velocity volumes are predicted. Then, the prediction horizon (number of future time slots to consider) is estimated corresponding to different weather conditions. ViCoWs can respond in real-time to weather conditions with correct collision avoidance warnings. Experiment results show that the mean absolute percentage error of our velocity prediction model is less than 11%. For non-congested traffic under heavy fog (very low visibility of 120 m), ViCoWS warns a driver by as much as 4.5 s prior to a possible future collision. If the fog is medium with a low visibility of 160 m, ViCoWs can give warnings by about 2.1 s prior to a possible future collision. In contrast, the Forward Collision Probability Index (FCPI) method gives warnings by only about 0.6 s before a future collision. For congested traffic under low visibility conditions, ViCoWS can warn a driver by about 1.9 s prior to a possible future collision. In this case, the FCPI method gives 1.2 s for the driver to react before collision.  
vehicle collision avoidance; data analytics; prediction; time-to-collision; back-propagation neural network; data fitting +
Footnote †: journal: Sensors
## 3 AHP/ANP with Shapley Values
### Modeling the Decision-Making Problem
#### 3.4.1 Decision-Making Variables  
The main decision-making variables in our model are as follows:  
1. Criteria weights (\(w_{i}\)): The relative importance of each criterion \(i\) in the decision-making problem, derived from the AHP/ANP.
2. Alternative scores (\(s_{ij}\)): The performance score of alternative \(j\) with respect to criterion \(i\), obtained from the AHP/ANP.
3. Coalition values (\(v(S)\)): The value or utility of each coalition \(S\) of alternatives, representing the cooperative contribution of the alternatives in the coalition.
4. Shapley values (\(\phi_{j}\)): The Shapley value of each alternative \(j\), quantifying its average marginal contribution to all possible coalitions.
# Graph-Based Resource Allocation for Integrated Space and Terrestrial Communications
## 5 Graph-Based RA in D2D Networks
### Graph Coloring-Based RA Methods
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Reference** & **Application** & \begin{tabular}{c} **Graph Model** \\ **Type** \\ \end{tabular} & \begin{tabular}{c} **Tasks Solved** \\ **via Graphs** \\ \end{tabular} & \
\begin{tabular}{c} **Graph Formulation** \\ **Method** \\ \end{tabular} &
\begin{tabular}{c} **Optimization** \\ **Assessment** \\ \end{tabular} \\ \hline
[68] & \begin{tabular}{c} Channel \\ allocation for \\ CUEs and \\ DUEs \\ \end{tabular} & Bipartite graph & \begin{tabular}{c} Channel \\ allocation \\ \end{tabular} & \
\begin{tabular}{c} Vertices—channels, \\ DUEs; edges—between \\ channels and DUEs; \\ weights—PF \\ \end{tabular} &
\begin{tabular}{c} \(R_{T}\) of up to \\ 12 b/s/Hz and \\ \(\beta=0.8\) for \\ algorithm \\ \end{tabular} \\ \hline
[69] & \begin{tabular}{c} Channel \\ allocation for \\ CUEs and \\ DUEs \\ \end{tabular} & Interference & Channel & \begin{tabular}{c} Vertices—small cells; \\ edges—between \\ interfering small cells \\ \end{tabular} & \
\begin{tabular}{c} Hungarian \\ algorithm \\ \end{tabular} &
\begin{tabular}{c} \(R_{T}\) of up to \\ 5 Gb/s for \\ \(N_{DUE}=\) \\ \(N_{CUE}=500\) \\ \end{tabular} \\ \hline
[70] & \begin{tabular}{c} Channel \\ allocation for \\ CUEs and \\ DUEs \\ \end{tabular} & Interference & Channel & \
\begin{tabular}{c} Vertices—CUEs and \\ DUEs; \\ edges—connecting the \\ interfering nodes \\ \end{tabular} &
\begin{tabular}{c} \(R_{u}\) up to \\ 2.5 Mb/s and \\ \(\beta=0.95\) for \\ algorithm \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table} 
Table 7: _Cont._such that the distance between two interfering nodes may be maximized. For greater efficiency, the tabu search heuristic algorithm [71] is used to obtain the solutions. It achieves significant gains for \(R_{T}\) as \(N_{DUE}\) increases, even though its convergence speed decreases significantly. In addition, notable improvement of the fairness index in comparison to other graph coloring methods has been reported. A graph-based user clustering of D2 Ds under the constraint of the outage probability of the CUEs is proposed in [61]. The channels are allocated preliminarily for the CUEs, and are orthogonal to each other. Each D2D pair constitutes a vertex in the graph, and there is an edge between two vertices if their achievable throughput is lower than a threshold. Channels represent colors, and are allocated through graph coloring so as to maximize the DUEs' satisfaction function, which is dependent on the DUEs' throughput requirements, their actual data rate, and on the number of neighboring vertices that use the same channel (it should be minimized). All D2D pairs that do not utilize duplicate channels form a cluster. The algorithm uses limited channel state information (CSI) to reduce the overhead. Simulation results show that CUEs outage probability stays minimal with the increase in the DUEs' number, while the satisfaction function is maximized when the interference tolerance among the DUEs is equal.
## 4 Conclusions  
In this study, different granulometric mining by-products were used to modify the PSD of a clayey soil to evaluate their potential in SRE building. Within this research, the following conclusions were obtained:  
* Both curing time and CEM dosage had a direct correlation with improvement in UCS. Mining by-products demonstrated significant potential in SRE building, as their addition to clayey soil resulted in higher UCS values compared to the UCS obtained from clayey soil alone. Moreover, the mix composed entirely of mining by-products achieved the highest UCS values.
* Unstabilized samples lost their integrity during exposure to water. CEM stabilization proved to be an effective solution for enhancing the water resistance of the mixes. The inclusion of mining by-products also showed its potential, as although the mixes did not fully meet the requirements in the soaked UCS and wetting and drying tests, the mix containing both mining by-products and clayey soil retained its integrity in water, unlike the samples composed solely of clayey soil. M3C5 successfully met the requirements in the soaked UCS and wetting and drying tests, further highlighting the great potential of mining by-products in SRE building.
* Cost-benefit and carbon footprint analyses showed that the combinations which performed best when evaluating both price and carbon footprint in relation to their mechanical properties were those using the mix composed entirely of by-products. This highlighted the potential of these by-products in the SRE building sector.  
This study highlights the potential of mining by-products for use in SRE building. These by-products exhibited excellent performance, as a mix entirely composed of mining by-products, combined with 5% CEM, met all established requirements. Additionally, they proved beneficial in enhancing the properties of a local soil. Further research would be valuable to explore the use of different stabilizers in combination with these by-products.  
Conceptualization, M.A.M.-A., C.P. and A.S.; methodology, P.V., R.A. and A.S.; validation, C.P. and A.S.; formal analysis, M.A.M.-A. and R.A.; investigation, M.A.M.-A.; data curation, M.A.M.-A. and P.V.; writing--original draft preparation, M.A.M.-A., P.V. and R.A.; writing--review and editing, C.P. and A.S.; visualization, M.A.M.-A., C.P. and A.S.; supervision, C.P. and A.S.; project administration, P.V. All authors have read and agreed to the published version of the manuscript. This research was supported by the Universidad Publica de Navarra via a doctoral grant to [PERSON] (1204/2022) in collaboration with Universite de Pau et des Pays de l'Adour.  
Not applicable.  
Data Availability Statement: The original contributions presented in the study are included in the article; further inquiries can be directed to the corresponding author.  
This research has been made possible thanks to the cooperation with the company Magnesitas Navarras S.A.  
The authors declare no conflicts of interest.
## 2 Materials and Methods
### Design of Notch Band Antenna  
To overcome the problem of band congestion due to the closely allocated band spectrums for various applications, the wideband antenna designed in the previous section is transformed into a notch band antenna. Usage of additional filters is the common way to notch the desire bands [21]. However, it may result in various drawbacks, including the requirement of additional matching circuits to match the impedance of the filter with wideband antenna [22]. Furthermore, it also requires a bigger area to fit the whole circuit allowing very little space for other components thus limits its usage in compact size devices [23]. Therefore, the researcher adopted various techniques including etching slots [24], loading metamaterials [25], insertion of Split Ring Resonator (SSR) [26], and stub loading techniques [27] to notch the desire bands.  
Furthermore, to avoid complex geometrical configuration, a simple yet effective technique to achieve a notched band is adopted, i.e., etching the slot in the radiator. One of the key parameters is to select the shape and position to place the slot, therefore, the shape and position of the slot must be chosen carefully to achieve a high value of VSWR to minimize the interference of the notch bands [28]. For the said purpose two V-shaped slots were used to achieve dual notch bands, the effective length (\(L_{S}\)) of the slot for desire frequency (\(f_{d}\)) can be calculated by [29]:  
\[L_{S(n)}=\frac{C_{o}}{2f_{d(n)}\sqrt{e_{eff}}} \tag{3}\]  
Figure 2: S\({}_{11}\) for rectangular shape monopole with and without truncated corners.  
where \((n)=1\), 2 which shows the number of slot while \(\varepsilon_{eff}\approx\frac{(\varepsilon_{r}+1)}{2}\). Moreover, for the proposed work \(L_{S1}=2\times L_{1}\) while \(L_{S2}=2\times L_{2}\). Figure 3 illustrates the comparison between simulated values of S\({}_{11}\) for wideband antenna and antenna with a single and dual notch. It could be observed that with a single V-shaped slot the antenna mitigates the band spectrum of 2.47-3.11 GHz having a maximum value of S\({}_{11}=-0.78\) dB at 2.82 GHz. Similarly, when two slots were etched, the antenna mitigates the two band spectrums of 2.48-2.96 GHz and 3.47-3.76 GHz. To have a better understanding of the slot to mitigate the desired frequency, current distribution plots were presented in Figure 4a,b. It could be observed from Figure 4a that for the first notch band the maximum current is around the bigger V-shaped slots, which causes the mitigation of the lower band. Similarly, the maximum current was observed along with a smaller V-shaped slot for the second notch band, which causes its mitigation from the resonating band spectrum.
## 4 Dynamics Analysis
 \tag{29}\]  
Substitute Equation (28) into the third equation of Equation (29) to obtain:  
\[F_{iz^{\prime\prime}}=-\bigg{(}\frac{ma_{i}}{C_{3}}-\frac{C_{1}}{C_{3}}F\sin \bigg{(}\varphi+i\frac{2\pi}{3}\bigg{)}+\frac{C_{2}}{C_{3}}F\cos\bigg{(} \varphi+i\frac{2\pi}{3}\bigg{)}\bigg{)}\quad(i=0,1,2)\]  
Therefore, using Formula (20) and omitting term \(\sin\theta\), substituting \(C_{3}\) simplifies to:  
\[R_{z^{\prime\prime}}=-6m\rho\omega^{2}tg\beta\cos 3\varphi \tag{30}\]  
When taking \(m=0.2\) Kg, \(\frac{2000\pi}{60}\) in radians per second, \(r=26\) mm, \(l=700\) mm, \(R_{z^{\prime\prime}}\) changing with \(\varphi\) as shown in Figure 10. As the output shaft rotates one cycle, the axial force exhibits three periods of variation with six zero-crossings. When \(\beta=0\), \(R_{z^{\prime\prime}}=0\); when \(\beta=5^{\circ}\), \(\beta=10^{\circ}\), the axial force almost coincides with the abscissa and can even be neglected; when \(\beta\leq 20^{\circ}\), the peak value of the axial force increases slowly; when \(\beta\leq 25^{\circ}\), the peak value of the axial force sharply rises, reaching over 8000 kilonewtons, increasing the system's instability, which should be overcome, while the periodic axial force variation will cause the system to generate judder and longitudinal vibration. Substitute Equation (31) into Equation (32) and solve to obtain:  
\[R_{x^{\prime}}=tg\beta m(a_{1}+a_{2}+a_{3})=-6m\omega^{2}\rho\sin\beta t\beta \beta\cos 3\varphi \tag{33}\]  
This is the same as:  
\[R_{y^{\prime}}=-\frac{1}{l}\Big{(}3m\rho^{2}\omega^{2}tg\beta\sin 6\varphi \Big{)} \tag{34}\]  
As shown in Figures 12 and 13, it can be observed that both \(R_{x^{\prime}}\) and \(R_{y^{\prime}}\) undergo periodic changes during the motion process. The frequency of variation for \(R_{x^{\prime}}\) is three times the angular frequency, while for \(R_{y^{\prime}}\), it is six times the angular frequency. When the \(\beta\) angle is the same, the peak value of \(R_{y^{\prime}}\) is much smaller than that of \(R_{x^{\prime}}\). Under different \(\beta\) values, the variation pattern of \(R_{x^{\prime}}\) and \(R_{y^{\prime}}\) is similar to \(R_{Z^{\prime}}\). When \(\beta=5^{\"}\), \(\beta=10^{\"}\), the support reaction force almost coincides with the abscissa. When \(\beta\geq 25^{\"}\), due to the sharp increase in the support reaction force, very strict requirements are imposed on the strength and stiffness of the input shaft. If \(R_{x^{\prime}}\) and \(R_{y^{\prime}}\) are too large, significant additional bending moments will be generated, leading to higher requirements for the strength and stiffness of the input shaft, while wear and vibration are inevitable, causing damage not only to the components themselves but also increasing the kinetic energy loss of the system.
# Numerical Analysis of Vibroacoustic Response of Timber Floor Panels Damped with Porous Materials
## 3 Finite Element Formulation of Sound Radiation of an Elastic Structure with a Poroelastic Layer
### Finite Element Discretization  
The resolution of the multiphysics problem considered in this work is conducted using the finite element method. Thus, introducing the vectors of nodal displacement of the elastic structure \(\stackrel{{\rightarrow^{E}}}{{U}}\) and the solid phase of the porous \(\stackrel{{\rightarrow^{S}}}{{U}}\). As well as the vector of nodal pressure in the fluid phase of the poroelastic \(\stackrel{{\rightarrow^{F}}}{{P}}\), the discretization of the bilinear formsof the previous variational formulation (Equations (5)-(7)) gives us the following coupled matrix system:  
\[\begin{bmatrix}[K_{E}]-\omega^{2}[M_{E}]&[C_{ES}]&[0]\\ \left[C_{ES}\right]^{T}&[K_{S}(\omega)]-\omega^{2}[M_{S}(\omega)]&-[C_{SF}]\\ \left[0\right]&-\omega^{2}[C_{SF}]^{T}&[K_{F}(\omega)]-\omega^{2}[M_{F}(\omega )]\end{bmatrix}.\begin{bmatrix}\stackrel{{\rightarrow}E}{{ \longrightarrow}}\\ \stackrel{{\rightarrow}E}{{\longrightarrow}}\\ \stackrel{{\rightarrow}E}{{\longrightarrow}}\\ \stackrel{{\rightarrow}}{{\longrightarrow}}\end{bmatrix}= \begin{bmatrix}\stackrel{{\rightarrow}}{{\longrightarrow}}\\ \stackrel{{\rightarrow}}{{\longrightarrow}}\\ \stackrel{{\rightarrow}}{{\longrightarrow}}\end{bmatrix} \tag{9}\]  
where \([K_{E}]\) and \([M_{E}]\), \([K_{S}]\) and \([M_{S}]\), \([K_{F}]\), and \([M_{F}]\) are the stiffness and mass matrices of the elastic structure, and the solid phase and the fluid phases of the porous material, respectively. \([C_{SF}]\) is a poroelastic phases-coupling matrix. \([C_{ES}]\) is the coupling matrix assuring that \(\stackrel{{\rightarrow}}{{\longrightarrow}}\stackrel{{ \rightarrow}}{{\longrightarrow}}\stackrel{{\rightarrow}}{{ \longrightarrow}}\stackrel{{\rightarrow}}{{\longrightarrow}} \stackrel{{\rightarrow}}{{\longrightarrow}}\) on \(\sum_{EP}\). \(\stackrel{{\rightarrow}}{{\longrightarrow}}\) is the vector of nodal forces applied to the structure. The system (9) is solved by a direct approach in the frequency domain, and at each frequency step the frequency-dependent matrices of the porous medium are updated. It leads simultaneously to the nodal displacements of the elastic structure and the porous solid phase and the nodal pressures in the fluid porous phase. The size of the system can be partially reduced by projecting the variables of the elastic structure onto a truncated projection basis calculated from the elastic-structure modes of the problem. However, due to complex dissipation mechanisms and frequency dependence of the structural and acoustic properties of the porous material, the associated eigenvalue problem is non-linear and prevents the use of reduced projection bases for this domain.