esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Shaking Table Tests
### Properties of the RUBBER Bearings  
To ensure the selected proper rubber bearings with good working conditions, horizontal performance tests were performed on a series of rubber bearings using a computer-controlled electro-hydraulic servo-pressure shear testing machine before the shaking table tests. Two rubber bearings, considered as one group, were placed above and below the shear plate, as shown in Figure 14. The shear deformation was caused by the horizontal movement of the shear plate. The shear plate tension was collected by the acquisition system of the machine. The displacement of the rubber bearing was measured using the GWC150 displacement device on the top of the shear plate. The vertical pressure during the test was set to the surface pressure of the rubber bearing as 6 MPa, and the axial compressive stress was maintained constant during the test. A total of 10 LNRs and 5 LNRs were tested.  
After analyzing the testing results, four LRBs and two LNRs with good working conditions were selected for a series of shaking table tests. The cross-section diagram and a photograph of an isolation rubber bearing used in our experiment are shown in Figure 15. The average horizontal equivalent stiffness (rubber shear strain \(\gamma=100\%\)) of the LRBs and LNRs was 0.296 kN/mm and 0.173 kN/mm, respectively. Typical hysteresis curves of the rubber bearings (LRB and LNR) are shown in Figure 16. The lateral stiffness of the seismic isolation was then obtained as the combined stiffness of the four LRBs and two LNRs, equal to 1.53 kN/mm (i.e., 0.296 \(\times\) 4 + 0.173 \(\times\) 2) which is 13.07\(\%\) lower than the theoretical value (1.73 kN/mm) obtained through similarity theory by multiplying the value of 8.64 kN/mm in the prototype structure with the geometric similarity ratio of 1:5. The detailed specification parameters and mechanical properties of the isolation rubber bearings can be found in Table 4, and these parameters are in line with the requirements of the GB 50011-2010 Code for seismic design of buildings [18]. Considering this minor difference between the practical and theoretical value, these rubber bearings could be used in the shaking table tests.  
Figure 14: Elastomeric isolator.  
Figure 15: Isolation rubber bearing: (**a**) Sectional view of the LRB (unit: mm); (**b**) isolation bearings.
# A Novel Optimization Design Method of Form Ginding Wheel for Screw Rotor
## 4 Experiment and Results
### Results and Discussion  
Since the grinding wheel wear is unavoidable during the grinding process, the machined profile can be measured in the middle of the screw surface (see Figure 11) to obtain precise comparison results. The results of the four experiments are shown in Figure 12, together with comparisons between the machined and theoretical profiles. The following observations are worth noting from Figure 12:  
1. In Experiments 1 through 4, the profile errors became increasingly large; the maximum profile error increased from \(\pm 6~{}\upmu\)m to \(\pm 8~{}\upmu\)m.
2. The areas with larger profile errors of the screw rotor corresponded to areas with a larger profile slope and curvature of the grinding wheel.
3. The results from Experiments 1 through 4 also showed that the surface integrity increasingly worsened, because the small length of the contact line leads to poor heat dissipation.  
Figure 12: Cont.  
Using the empirical method, the profile error is large when the installation angle is equal to the lead angle. Grinding wheels are more prone to wear when the slope and curvature of the shaft section profile of the grinding wheel are large. In addition, the longer the contact line, the better the grinding surface integrity. Based on the above findings, it can be found that the profile error is significantly reduced compared with the empirical method during the grinding process of a female rotor, which indicates that the proposed optimization design method can provide better grinding performance for form grinding wheels used with screw rotors than is possible when using the empirical method. To the best of the authors' knowledge, this is the first time that the grinding performance of the grinding wheel is related to the installation parameters, and the grinding performance of the grinding wheel is optimized in the design stage.
# Exploring Channel Properties to Improve Singing Voice Detection with Convolutional Neural Networks
## 2 Methods
### Multi-Scale Input Channels
#### 2.2.1 Motivation  
In this study, the aim was to improve the SVD performance using the CNNs with feature learning by feeding spectrograms. Here, there is a precondition that the spectrogram should be as correct and complete as possible to represent the original musical signal. The representation quality of the spectrogram depends mainly on the time resolution and the frequency resolution at the stage of STFT. It is worth noting that the time resolution and the frequency resolution restrict each other, and that the best frequency resolution cannot be obtained simultaneously with the best time resolution. In general, these two resolutions are contingent on the size of the window function of STFT. We refer to size or duration as \"scale\" in this paper. In practice, different musical signals need different scales because they have their own predominant frequency bands and time structures. The better the scale adapts to the signal, the better the representation. We show the typical scales, and the corresponding time and frequency resolutions, in the Table 1 below, where the signal sampling rate is 22,050 Hz.  
The frequency resolutions in the table above may be suitable for most songs. However, which is the best? The answer is different for different songs. The conventional method used to resolve this problem is to choose the best scale after testing all the scales on the datasets. We propose to combine the multi-scale spectrograms as the input channels. Given the multi-scale input channels, in which some representations may be suitable for the signal while others may be unsuitable, the CNNs can learn and choose the optimal representation for the task.
_Appl. Sci._**2015**, \(5\), 174-186; doi:10.3390/app5030174  
_Applied sciences_  
**ISSN 2076-3417**  
www.mdpi.com/journal/applsci  
_Article_  
_In operando_ Detection of Three-Way Catalyst Aging by  
a Microwave-Based Method: Initial Studies  
**[PERSON] 1,2, [PERSON] 2 and [PERSON] 1,*  
1 Bayreuth Engine Research Center (BERC), Zentrum fur Energietechnik (ZET), Department of  
Functional Materials, University of Bayreuth, 95445 Bayreuth, Germany;  
E-Mail: [EMAIL_ADDRESS]  
2 Umicore AG & Co. KG, 63403 Hanau-Wolfgang, Germany;  
E-Mail: [EMAIL_ADDRESS]  
* Author to whom correspondence should be addressed;  
E-Mail: [EMAIL_ADDRESS]; Tel.: +49-921-55-7400; Fax: +49-921-55-7405.  
Academic Editor: [PERSON]  
_Received: 4 June 2015 / Accepted: 20 July 2015 / Published: 29 July 2015_  
**Abstract:** Initial studies on aging detection of three way catalysts with a microwave cavity perturbation method were conducted. Two physico-chemical effects correlate with the aging state. At high temperatures, the resonance frequencies for oxidized catalysts (\(\lambda=1.02\)) are not influenced by aging, but are significantly affected by aging in the reduced case (\(\lambda=0.98\)). The catalyst aging state can therefore potentially be inferred from the resonance frequency differences between reduced and oxidized states or from the resonance frequency amplitudes during lambda oscillations. Secondly, adsorbed water at low temperatures strongly affects the resonance frequencies. Light-off experiment studies showed that the resonance frequency depends on the aging state at temperatures below the oxygen storage light-off. These differences were attributed to different water sorption capabilities of differently aged samples due to a surface area decrease with proceeding aging. In addition to the aging state, the water content in the feed gas and the temperature affect the amount of adsorbed water, leading to different integral electrical material properties of the catalyst and changing the resonance properties of the catalyst-filled canning. The classical aging-related properties of the catalyst (oxygen storage capacity, oxygen storage light-off, surface area), agreed very well with data obtained by the microwave-based method.  
**Keywords:** three-way catalyst (TWC); on-board diagnosis (OBD); oxygen storage capacity (OSC); microwave cavity perturbation; lambda-probe
# Optimal Steady-State Range Prediction Filter for Tracking with LFM Waveforms
## 4 Performance Evaluation  
We next investigate the performance of the LFM \(\alpha\)-\(\beta\) filter with the proposed gain design method using theoretical steady-state analyses and numerical simulations assuming radar tracking of a maneuvering target. Both the proposed and the conventional maximum RMSE-based methods [10] are compared.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Design Methods** & **Preset Parameter** & **Evaluating Function** & **Process Noise** \\ \hline Tracking index-based method of [8] & \(\Gamma\) & Not used & Random acceleration \\ Tracking index-based method of [9] & \(\Gamma\) & Not used & Arbitrary random parameter \\ Maximum root mean square error (RMSE) [10] & \(\Gamma_{\rm D}\) & Equations (10)–(12) & Random acceleration \\ Proposed method & \(\Gamma_{\rm D}\) & Equation (17) & Not assumed \\ \hline \hline \end{tabular}
\end{table}
Table 1: Summary of the conventional and proposed design methods.
# ALPINE: Active Link Prediction Using Network Embedding
## 3 The ALPINE Framework
### Active Link Prediction Using Network Embedding--The Problem  
After embedding the PON, we can use the model to predict the unknown link statuses. Often, however, an \"oracle\" can be queried to obtain the unknown link status of node pairs from \(U\) at a certain cost (e.g., through an expensive wet lab experiment). If this is the case, the query result can be added to the known part of the network, after which the link predictions can be improved with this new information taken into account. By carefully querying the most informative nodes, active learning aims to maximally benefit from such a possibility at a minimum cost. More formally, this problem can be formalized as follows.  
**Problem 1** (Alpine).: _Given a partially observed network \(\mathcal{G}=(V,E,D)\), a network embedding model, a budget \(k\), a query-pool \(P\subseteq U\), and a target set \(T\subseteq U\) containing all node pairs for which the link statuses are of primary interest, how can we select \(k\) node pairs from the pool \(P\) such that,after querying the link status of these node pairs, adding them to the respective set \(E\) or \(D\) depending on the status, and retraining the model, the link predictions made by the network embedding model for the target set \(T\) are as accurate as possible?_  
The pool \(P\) defines the candidate link statuses, which are unobserved but accessible (i.e., unknown but can be queried with a cost), while the target set \(T\) is the set of link statuses that are directly relevant to the problem at hand. Of course, in solving this problem, both the link prediction task and the active learning query strategy should be based only on the observed information \(K=E\cup D\).  
The problem is formalized in its general form and can become specific depending on the data accessibility (represented by \(P\)) and the link prediction task (represented by \(T\)). The pool \(P\) may contain all the unobserved information or only a small subset of it. Sets \(T\) and \(P\) may coincide, overlap non-trivially, or be disjoint, depending on the application. We experiment with various options in our quantitative evaluation in Section 5.3.
## 4 Proposed Scheme
### Mutual Authentication Phase  
After sharing the secret key, the mutual authentication process is performed to ensure the legitimacy of the remote users. We propose a simple method of mutual authentication using a \"Hash-based Message Authentication Code\" (HMAC) and a symmetric session key. The HMAC generates a fixed-length message code that can be used in the authentication. The hashing value depends upon the hashing algorithm [47]. The server and doctor's device generate HMAC by using an IP address, a session key \(S_{K}\), and a random number in hashing algorithm SHA-256, as shown in Equation (8) and Equation (9), respectively.  
Random numbers and session keys ensure the freshness of the HMAC because, in every new session, random numbers and session keys will be changed.  
\[HMAC_{D}=SHA-256\ (\mathit{IP\ Address}_{D}\parallel N_{D},K_{S}) \tag{8}\]  
\[HMAC_{S}=SHA-256\ (\mathit{IP\ Address}_{S}\parallel N_{S},K_{S}) \tag{9}\]  
The server and doctor's device send HMAC to each other for mutual authentication. Both sides calculate HMAC and verify it. If any one side does not verify it, then the established connection is terminated immediately on either side. If authentication is performed, then the server fetches the patient's record of that doctor and displays it on the device. For security reasons, the doctor can only access their patient's records remotely.  
Figure 3: Secret key exchange and authentication processes.
# Composition and Basic Physical Properties of the Phobos Surface: A Comprehensive Review
## 3 Hypotheses of Formation  
### Capture Hypothesis  
The capture hypothesis posits that Phobos is a \"captured\" asteroid. The main arguments supporting the capture scenario are the morphological, physical, and spectroscopic similarities between the moon of Mars and primitive asteroids [14,16]. The resemblance between the surface spectra of the Martian moon and D- or T-type asteroids suggests that the moon is composed of the same material as these asteroids, namely, carbonaceous material [1]. This scenario would explain its low density and low albedo.  
Several possible scenarios have been proposed that would be consistent with the capture hypothesis and the current orbit. The first suggests that the body was captured into an equatorial orbit. However, maintaining an orbit in the equatorial plane would require a rapid change in the distance between the orbit and Mars (approximately 13R\({}_{\rm M}\), where R\({}_{\rm M}\) is the average radius of Mars, equal to \(\sim\)3396 km) shortly after its capture, which seems challenging given how slowly the orbit eccentricity is modified by tidal effects [1,14,17]. The second solution posits that the orbit, after the body's capture, was quickly inclined in the equatorial plane and rounded by the scattering of resistance in the planetary nebula [18,19]. However, studies of the resistance effect have not yet shown whether the density profile and the lifetime of the nebula are consistent with the requirements of the capture scenario [14].  
It should be noted that if the Martian moons (Deimos and Phobos) were indeed captured, either they shared the same original composition (originating from the same body) or they underwent extensive cosmic weathering, resulting in the formation of nearly identical surfaces [4].  
However, the capture hypothesis is considered less likely due to the fact that dynamic capture models require specific conditions, including aerodynamic drag in the early proto-atmosphere of Mars [4,10,18,20]. Additionally, the nearly equatorial and nearly circular orbit of Phobos is considered unlikely for this scenario [1,10,14,17]. Furthermore, such a scenario would require the consideration of a mechanism that would change the orbit of the Martian satellite post-capture to the one currently observed. One possible mechanism for achieving this is the dissipation of orbital tides [14,21]. However, this mechanism would not be sufficient for Deimos (Mars' second moon) [14,22]. Additionally, the orbital changes induced by tides require a very low tidal quality factor, more suitable for icy material than for rocky material [1].  
\begin{table}
\begin{tabular}{c c c c} \hline
**Semi-Major Axis** & **Eccentricity** & **Inclination to the Equator** & **Orbital Period** \\ \hline
9375 km (2.76 R\({}_{\rm M}\)) & 0.0151 & 1.076\({}^{\circ}\) & 7 h 39\({}^{\prime}\) 19.47\({}^{\prime\prime}\) \\ \hline \end{tabular}
\end{table}
Table 1: The general orbit data of Phobos [14,15].
# Adaptive Threshold-Aided K-Best Sphere Decoding for Large MIMO Systems
## 2 Background
### Sphere Decoder for MIMO  
The SD algorithm aims to reduce the complexity of ML detection by searching only inside a sphere [10; 11; 12]. Taking the QR decomposition of the channel matrix as \(\mathbf{H}\) = \(\mathbf{QR}\), where \(\mathbf{Q}\) is an \((M\times N)\) matrix satisfying \(\mathbf{Q}^{T}\mathbf{Q}=\mathbf{I}\), and \(\mathbf{R}\) is an upper triangular matrix of size \(N\times N\), (3) transforms into the minimization of \(\hat{\mathbf{s}}_{\text{ML}}=\left\|\mathbf{z}-\mathbf{Rs}\right\|^{2}\), where \(\mathbf{z}=\mathbf{Q}^{T}\mathbf{y}\). The SD examines all signal vector candidates inside a sphere to generate the detection output  
\[\hat{\mathbf{s}}_{\text{SD}}=\arg\min_{\mathbf{s}\in D}\|\mathbf{z}-\mathbf{ Rs}\|^{2},D=\left\{\mathbf{s}\in\Omega^{N}\big{|}\left\|\mathbf{z}-\mathbf{Rs} \right\|^{2}\leq C_{0}^{2}\right\}, \tag{4}\]  
where \(C_{0}\) denotes the initial radius of the sphere. At layer \(i\) of the SD, we use the condition  
\[\left|z_{i}-\sum_{j=i}^{N}r_{i,j}s_{j}\right|^{2}\leq d,\ d=C_{0}^{2}-T( \mathbf{s}^{(i+1)}) \tag{5}\]  
to determine a set of surviving paths \(\{\mathbf{s}^{(i)}\}\), where \(\mathbf{s}^{(i)}=[s_{i}^{(i)},s_{i+1}^{(i)},\ldots,s_{N}^{(i)}]^{T}\) is a surviving path at layer \(i\), and \(T(\mathbf{s}^{(i)})\) is the accumulated path metric of \(\mathbf{s}^{(i)}\), which is defined as  
\[T(\mathbf{s}^{(i)})=\sum_{k=i}^{N}\left|z_{k}-\sum_{j=k}^{N}r_{k,j}s_{j}^{(i)} \right|^{2}. \tag{6}\]  
In this work, the initial radius is chosen as \(C_{0}=\sqrt{\gamma N\sigma^{2}}\), where \(\gamma\geqslant 1\) is typically set to nearly guarantee that the true solution exits in the sphere [8]. The radius is updated when the search process reaches the leaf layer [13]. The iterative search of SD continues until only one point is left inside the sphere and is a solution to (4).
## Abbreviations  
The following abbreviations are used in this manuscript:  
\begin{tabular}{l l l l} AI & Artificial Intelligence & & \\ AOTF & Acousto-Optical Tunable Filter & & \\ ASIC & Application-Specific Integrated Circuit & & \\ COTS & Commercial-Off-The-Shelf & & \\ DAC & Digital-to-Analog Convertor & & \\ DDS & Direct Digital Synthesis & & \\ DE & Diffraction Efficiency & & \\ ECSS & European Cooperation for Space Standardization & & \\ FPGA & Field Programmable Field Array & & \\ \end{tabular}  
\begin{table}
\begin{tabular}{l c c c} \hline \hline \multicolumn{1}{c}{**RF Generation Technique**} & \multicolumn{2}{c}{**Advantages**} & \multicolumn{2}{c}{**Disadvantages**} \\ \hline \multirow{3}{*}{Integrated PLL design} & - & fully digital design & & \\  & - & low mass & - & output filtering needed \\  & - & low PCB area usage & - & limited flight heritage \\  & - & compliant with requirements & & \\ \hline \multirow{3}{*}{DDS inside an FPGA} & - & proven digital design & - & for UV frequency range, a frequency \\  & - & flight heritage & & doubler is needed \\  & - & compliant with VIS and NIR & - & output filtering needed \\  & & frequency range) & - & complex PCB design with FPGA \\ \hline \multirow{6}{*}{SSB mixing} & \multirow{6}{*}{-} & \multirow{6}{*}{proven analog design} & - & complex output filtering is needed \\  & & & - & complex design \\  & & & - & high power consumption \\  & - & & high PCB area usage \\  & - & compliant with requirements & - & high mass \\  & & & - & low output power level \\  & & & - & harmonic suppression \(<-30\) dBc is \\  & & & & marginally achieved \\ \hline \multirow{2}{*}{DDS and DAC chip repackaging} & - & fully digital design & - & high cost \\  & - & compliant with the requirements & - & possible outgassing issues \\ \hline \multirow{6}{*}{ASIC} & - & fully digital design & - & very high cost \\  & - & low mass & - & limited market available \\ \cline{1-1}  & - & low PCB area usage & - & long lead time \\ \cline{1-1}  & - & compliant with requirements & - & ITAR/EAR restrictions \\ \hline \hline \end{tabular}
\end{table}
Table 4: RF generator techniques comparison table.
## 3 Results and Discussion
### Regeneration and Reuse  
Considering the cost-effective application of Mag-PVP in wastewater treatment, the possibility of regeneration and reusability was further investigated. Desorption of BPA in different organic solvents, such as methanol, ethanol, toluene and cyclohexane, was studied. Results found that methanol had the best desorption efficiency [40]. Methanol was selected for the regeneration of Mag-PVP and the data were shown in Figure 10. Mag-PVP can be recycled at least twelve times without the expense of adsorption capacities. After twelve cycles, the adsorption capacity is around 96%. Excellent reusability performance indicated that Mag-PVP can be used in practical applications for removal of BPA.  
Figure 10: Regeneration performance of Mag-PVP (BPA concentration = 5 mg/L; adsorbent dosage = 0.2 g/L; shaking time = 4 h). Error bars represent standard deviation values from three replicates.  
Figure 9: The adsorption of BPA on Mag-PVP in different water samples. D, T, S, and E represent deionized water, tap water, surface water, and the effluent water in sewage treatment plants, respectively (BPA concentration = 10 mg/L; adsorbent dosage = 0.2 g/L; shaking time = 4 h). Error bars represent standard deviation values from three replicates.
# Optical Design and Stray Light Analysis of Underwater Spectral Radiometer
## 4 Stray Light Suppression and Simulation Analysis
### Analysis and Calculation of Stray Light Suppression Index
* Surface solar spectral irradiance \(E_{S}(490)=1.2\) w/cm\({}^{2}\).um
* Air-to-sea interface transmittance \(T_{s}=0.98\)
* Diffuse attenuation coefficient in oceanic-type water \(K(490)=0.05\) m The instrument's position below the sea surface is z = 20 m
* Pixel area \(A_{\rm d}=2.5\) mm \(\times\) 25 \(\mu\)m; Quantum efficiency \(\eta(\lambda)=0.5\)
* The transmittance of the optical system for irradiance measurement: \(T_{\rm c}=0.02\%\) \(T_{c}\) is the result of the cosine corrector transmittance combined with fiber optic bundle coupling. * Grating diffraction efficiency \(\tau_{o}(\lambda)=0.4\)
* Detector dark current \(I_{dark}=0.3\)pA  
When the proportion of stray light to signal light changes during an integration time of 1 s, the variation in the system's signal-to-noise ratio is as shown in Figure 9.  
From Figure 9, it can be observed that when the stray light signal is less than 1% of the signal light magnitude, the signal-to-noise ratio of the underwater spectral radiometer exceeds \(10^{2}\), meeting the instrument's design requirements.