esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 The FSPR System and Temperature Measuring Method
### Temperature Measuring Method  
In this project, a remote monitoring system developed at Tongji University was used for temperature monitoring, including the temperatures of the frozen soil and the brine freezing loop. This remote monitoring method, based on a 1-Wire (Maxim Integrated Products, San Jose, CA, USA) bus system, makes automatic and continuous computer monitoring possible and contributes to observing the development of the frozen soil wall and judging the freezing effect of FSPR. More details about the monitoring system can be found in Reference [22].  
For the monitoring of soil temperature, 32 measuring faces were arranged longitudinally along the tunnel, which were numbered as 1 to 32 from east to west. The distance between two measuring faces was about 8 m. A typical measuring face N is shown in Figure 3. The temperature measurement points of each measuring surface were classified as the wall temperature measuring point and the soil temperature measuring point. The latter was installed through the temperature measuring holes, which were drilled from inside the steel pipes. Furthermore, 3-7 soil temperature measuring points were arranged in each hole to determine the development and changes of the frozen soil wall. The naming conventions of measuring points were as follows: D + steel pipe number - measuring face number - S/B + measuring point number (where S means the soil temperature measuring point, and B means  
Figure 1: Schematic of the tunnel section.  
Figure 2: Schematic of the freezing scheme.  
the wall temperature measuring point). For example, D06-15-S3 represents the third measuring point installed from the sixth steel pipe at the 15 th measuring face.  
The measured temperature data of different stages and multiple areas are analyzed later. Figure 4 is a schematic of the selected area and measuring points. The blue boxed area represents the selected area for analysis during the active freezing period, and the red one is that for the excavation period.
# Speaker Diarization: A Review of Objectives and Methods
## 3 Analysis of Speech Signals
### Simple Spectral Measures  
The time waveform of speech may serve directly as input to SD techniques, as a way to simplify SD algorithms. However, the direct utility of speech in time is limited; owing to the high level of encoding in speech, simple measures of overall intensity and periodicity are useful, but the dependence of speech time waveforms on spectral phase variations, which have little direct link to speech message information, has led most speech classification applications, including SD, to use analysis focussed on amplitude spectra.  
The simplest spectral method to analyze data is the _discrete Fourier transform_ (DFT). It shows energy versus frequency [26], converting \(N\) time samples (inside a temporal window that is shifted uniformly to handle the non-stationarity of speech) into \(N\) samples (256-251) in frequency. For most classification problems, a disadvantage of the basic DFT is that it has excessive detail. Additional processing (such as data reduction or pattern extraction) is generally needed.  
A variant of DFT that is often used for speech classification is _filter bank energies_ (FBEs); they smooth DFT amplitudes over restricted ranges of frequency using bandpass filters. The nonlinear Mel scale is often used in the frequency scale [27]. This has equal-bandwidth filters to 1 kHz, and then spaces logarithmically, which matches the reduced resolution that the human auditory system has at increasing frequency (which, in turn, follows the tapering of the basilar membrane in the inner ear). ASR often uses 20-100 FBEs, which reduces data from a 256- or 512-sample DFT, while at the same time retaining enough spectral information.
# A Novel Virtual Sensor for Estimating Robot Joint Total Friction Based on Total Momentum
## 3 Simulation and Analysis
### Payload Experiment
#### 4.3.3 Comparison with the Classical Friction Model  
In order to compare the proposed algorithm with the other friction model, comparison experiments were conducted. The Coulomb and viscous friction model is classical and common in real applications. Furthermore, less friction parameters need to be identified in this model, so it is selected as the comparison friction model. The Coulomb and viscous fiction parameters were tuned manually to obtain smaller trajectory tracking errors as far as possible. Finally, the friction model was designed as  
\[\tau_{f,m}=-\Big{(}F_{c}\text{sgn}(\dot{\theta})+F_{v}\dot{\theta}\Big{)}, \tag{24}\]  
where \(F_{c}\) is the Coulomb friction coefficient and is tuned to \(2.8\times 10^{-3}\) Nm.s/rad, \(F_{v}\) is the viscous friction coefficient and is tuned to \(1.1\times 10^{-3}\) Nm.s/rad, \(\dot{\theta}\) is the motor velocity, and \(\tau_{f,m}\) is the motor-side friction torque.  
The estimated friction torque (blue curves) calculated by (23) is shown in Figures 14a and 15a under low-velocity and high-velocity conditions, respectively. The RMSE of motor trajectory tracking static errors are listed in Table 6 and shown in Figure 14b,c and Figure 15b,c under low-velocity and high-velocity conditions, respectively. It can be found that the RMSE of motor velocity tracking static errors, after compensating for the friction torque estimated by the proposed method, are always less than those after compensating for the friction torque estimated by the Coulomb and viscous friction model, no matter whether the motor is in low-velocity and high-velocity conditions. This shows that the friction torque estimated by the proposed method is more accurate than that estimated by the Coulomb and viscous friction model. Notably, the Coulomb and viscous friction model cannot describe the complete and complex friction properties. However, more accurate friction torque can be observed by the proposed observer. Therefore, the proposed friction observer exhibits more accurate friction estimation than the Coulomb and viscous friction model. Finally, it should be also noted that only one parameter \(K_{\mu}\) in the proposed method needs to be tuned; however, two parameters are needed in the classical Coulomb and viscous friction model.
## 4 Results and Analysis  
### Comparison between the Simulation and Experimental Results  
In this section, the FSI model is verified from two aspects. On the one hand, the flow field is verified by the pressure variation in the cylinder. On the other hand, the structural field is verified by the movement of the suction valve. The compressor operating conditions were as follows: the suction temperature was 20 \({}^{\circ}\)C, the suction pressure was 0.103 MPa (atmospheric pressure), and the discharge pressure was 0.4 MPa.  
The difference of the p-\(\theta\) diagram between the experiment and simulation is shown in Figure 10a. The pressure variation of the FSI model was coincident with the experiment results. In particular, there were three pressure fluctuations during the discharge phase in both the simulation and experiment results. It was proven that the flow field simulation results of the FSI model were reliable. In addition to the p-\(\theta\) diagram, the movement of the need valve was another key point for verifying the FSI model, as shown in Figure 10b. In the suction phase, the opening and closing angles of the suction need valve were almost identical. Moreover, the simulation results of the need valve flutter were in good agreement with the experimental results. It was proven that the simulation results of the structure field of the FSI model were reliable.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Structure Parameter** & **Value** & **Structure Parameter** & **Value** \\ \hline Type & Single action & Piston stroke (mm) & 30 \\ Displacement (m\({}^{3}\cdot\)h\({}^{-1}\)) & 9.8 & Connecting rod length (mm) & 120 \\ Cylinder diameter (mm) & 68 & Rotation speed (r\(\cdot\)min\({}^{-1}\)) & 1500 \\ \hline \hline \end{tabular}
\end{table}
Table 4: The structure parameters of the air compressor in the experiment.  
Figure 9: Test facility for the compressed air system.
## 2 Methodology
### Loss Functions, Optimizers, and Schedulers
#### 2.3.2 Optimizers  
In this study, the optimization process was carefully tailored using specific combinations of optimizers and learning rate schedulers to make sure that each model learned efficiently and adapted well throughout training.  
Optimizers were chosen based on how they handle gradients and adjust learning over time.  
* SGD (Stochastic Gradient Descent), enhanced with momentum (set to 0.9) and weight decay, offered a steady and reliable learning path. By accumulating gradients across iterations, it helped the model converge smoothly.
* Adam brought adaptive learning by adjusting learning rates based on both the average and variance of past gradients, which is especially helpful for handling sparse or noisy updates.
* AdamW, a refined version of Adam, separated weight decay from the update step, leading to better regularization and often improved generalization.
## 3 Results and Discussion
### Color Measurement  
Table 4 shows the effect of sea buckthorn extract addition on the color and opacity of the films. The brightness (L*) of the films decreased with the addition of 0.01 g and 0.05 g scCO\({}_{2}\) extract per 1 g of PBS (63.90 \(\pm\) 0.34 and 61.94 \(\pm\) 0.10, respectively) and increased slightly for Chl extracts, especially at 0.05 g per 1 g of PBS concentration (64.75 \(\pm\) 0.08). The red (a*) and yellow (b*) tints increased in the extract-modified films, especially for the scCO\({}_{2}\) extract, which may be due to the higher concentration of dyes in these extracts. The total color change (\(\Delta\)E) was highest for PBS-CO\({}_{2}\) 0.05 (7.97 \(\pm\) 0.25), indicating the greatest effect on film color. The yellowish index (YI) increased significantly with the scCO\({}_{2}\) extract (up to 107.67 \(\pm\) 0.65), confirming its coloring properties, while the Chl extract had less effect on this parameter. Opacity also increased, especially for PBS-CO\({}_{2}\) 0.01 (18.80 \(\pm\) 1.56), indicating greater light scattering in these samples.  
[PERSON] et al. investigated PVA films modified with citric acid and sea buckthorn leaf extract and observed an increase in the opacity of films with the addition of the extract; however, at the additive concentrations tested (0%, 2%, 4%, and 6%), only the 4% concentration showed a statistically significant increase (\(p\) < 0.05) [22].
## 2 Related Works
### GIS-Based Systems  
[PERSON] et al. (2012) applied a GIS to develop a novel mobile recommendation system for tourism [(20)]. The system contained a recommendation engine and a three-dimensional (3D) mobile GIS architecture. These capabilities provided the user with location-based recommendations and access to a 3D-map-based interface. [PERSON] et al. (2019) developed a location-aware recommender system using volunteered geographic information (VGI) [(21)]. This system consisted of two phases: VGI collection and filtering, and location-based recommendation. In this system, the VGI is collected and purified according to position accuracy and user contribution history. Subsequently, the system applies filtered VGI and a content-based filtering strategy to recommend the best restaurant based on user preferences. [PERSON] et al. (2020) proposed a novel spatiotemporal analysis based on Flickr data to construct a fine-grained pattern for tourists [(22)]. First, a temporal variation analysis was performed. Second, the study employed kernel density estimation to analyze the seasonality of tourism. Third, the correlation between attraction grade and popularity was measured using both qualitative and quantitative methods. Finally, the space-time cube method was employed to visualize the identified pattern. [PERSON] et al. (2020) employed a method to assess the emotions of visitors using social media messages about theme parks [(23)]. This was achieved using geospatial analysis and social media analytics. In addition, the place of emotion gathering was visualized. Different statistics were used in this study. The circumplex model of affect proposed by [PERSON] was used to analyze tweets with one or more emotional words. Furthermore, GIS exploratory analysis and text mining were used to assess the emotions in each quadrant of tweets. In addition, based on significant clustering of emotions in quadrants, the areas of riding attraction in the theme park were determined. [PERSON] et al. (2020) developed a recommendation system for sightseeing spots [(24)]. The system was based on recommended social networking services, a web-based GIS, and recommendation systems. The recommendation component was developed using two methods for selecting the POIs for a tourist: knowledge-based recommendation, and collaborative recommendation.  
Notably, geospatial systems require personalization based on contextual information. Such systems can be incorporate analytical methods such as MCDM to perform functions such as recommending or selecting tourist POIs. This enables the system to consider multiple factors, which may increase user satisfaction during POI selection.
## 4 Conclusions  
In conclusion, the existing 132 kV transmission lines under the case study were proposed to uprate to the new voltage level of 275 kV using the voltage uprating method. The techniques involve in voltage uprating are by increasing insulation strength and improving air conductor clearances. It is found that the voltage uprating of the existing 132 kV transmission lines fulfilled all the electrical clearances such as phase-to-earth, phase-to-phase and phase-to-ground with consideration of still air, normal wind, and extreme wind conditions. It was also revealed the electrical clearances of phase-to-phase and phase-to-ground are almost double the required minimum requirement needed for 275 kV transmission lines operation. It was believed the margin of electrical clearances ought to be sufficient for operating maximum load conditions.  
A simulation study was carried out to evaluate the insulation strength of the proposed model by considering transient overvoltages, power frequency, and several conditions. Based on the simulations results under still air and normal wind conditions, it is found the voltage magnitude at BIL, and BIL +10% during backflashover events are much lower than the estimated CFO. For backflashover and extreme wind conditions under the case study, no voltage magnitude at all BIL was found to be exceeded the estimated CFO that could potentially cause flashover. Meanwhile, for shielding failure events under still and wind conditions, there is a significant difference in the percentage between the estimated CFO and all level BIL cases are ranging from 15.9 to 71.3%. It is worth to mention that the proposed voltage uprating of the existing 132 kV transmission line satisfies the insulation strength at BIL for all cases and is believed fit to operate for a 275 kV transmission line.  
Conceptualization, S.F.M.N. and M.Z.A.A.K.; resources, A.M.A. and M.S.A.R.; writing--original draft preparation, S.F.M.N.; writing--review and editing, S.F.M.N., M.Z.A.A.K., M.O. and N.M.Z.; supervision, M.Z.A.A.K., A.M.A. and M.O.; funding acquisition, M.Z.A.A.K., A.M.A. and M.O. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Universiti Tenaga National through the UNITEN Bold Grant.  
Not applicable.  
The authors would like to thank Tenaga National Berhad (Grid Maintenance) team for their kind support on the data.  
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
# Genesis and Magmatic Evolution of the Gejiu Complex in Southeastern Yunnan, China
## 4 Results
### Geochemistry
#### 4.2.3 Rare Earth Element (REE) Geochemistry
Concurrently, fractional crystallization during magmatic evolution led to the crystallization and removal of heavy rare earth element (HREE)-rich minerals (e.g., garnet, amphibole), leaving the residual magma significantly enriched in light rare earth elements (LREEs).
# Flexible Antennas for a Sub-6 GHz 5G Band:
## 2 Materials for a Flexible Antenna  
Flexible antennas are made of two kinds of materials: conductive materials and substrates. Both conductive materials and substrates need to be chosen in such a way that the antenna fabricated using these materials should show good radiation characteristics. In the design of any flexible antenna, the choice of substrate material is very important. The substrate is selected based on its dielectric characteristics, and capacity to bear mechanical deformations including bending, crumpling, and mechanical stresses. Conductive materials, on the other hand, are chosen in terms of their good electrical conductivity, resistivity, tensile strength, and ability to integrate with flexible substrates [16].
# A Transformer-Less Buck-Boost Grid-Tied Inverter with Low Leakage-Current and High Voltage-Gain
###### Abstract
The H5 inverter suppresses the leakage current by adding one power switch to keep CMV as constant [19]. The oH5 inverter improves the voltage stresses of the power components by adding one additional switch to clamp CMV to be half of the H5 inverter [21]. A non-isolated inverter with step-up/down capability is proposed in the literature [17], in which a power switch is added to control the freewheeling path of inductor current. This inverter connects the utility-line to the negative end of the PV array, which can suppress leakage current. However, the disadvantage of this inverter is that it operates with the principle of buck-boost. The energy needs to be saved in the inductor before being transmitted; it reduces the conversion efficiency and limits the output power. Figure 1: The PV grid-tied system with two stage of energy processing. Figure 2: The PV grid-tied system with a single stage of energy processing. Based on the previous considerations, a transformer-less buck-boost grid-tied inverter with low leakage-current and high voltage-gain is proposed. Two dual-switch buck-boost converters with coupled inductors are connected in parallel to generate a unipolar half-wave, and two low-frequency switches are adopted to switch the output polarity. When the proposed circuit operates in the step-up mode, the primary side of the coupled inductor is charged first, and then the primary side and the secondary side are discharged in series, which can increase voltage-gain. In addition, due to the use of two buck-boost converters in parallel, the polarity unfolder is able to be effectively simplified as two switches to reduce conduction losses. The mains can be directly attached to the negative end of the PV array to suppress leakage current. In addition, the proposed inverter also has the following features:  
1. Only single energy-processing is required, and high-frequency switching is only performed in one MOSFET in each mode, which can effectively improve efficiency;
2. The inverter operates with the principle of boost or buck, so that part of the energy can be directly transmitted to improve efficiency;
3. The proposed inverter is feasibility for PV grid-tied systems with wide-range voltage changes because of its step-up and step-down capabilities.
# Performance of Concrete with Waste Granite Powder: The Effect of Superplasticizers
## 4 Results and Discussion
### Density of Fresh Concrete  
Figure 8 shows that the fresh-density of the mix is maximum when 5% of WGP introduced, as a result of better cement particle dispersion of the granite powder. At more than 5%, the density of concrete decreases due to lower specific gravity of WGP than cement. The downward trend in high substitution ratios continues, which contradicts the results of [44]. They reported an increase in density and strength at 30% substitution ratio. The difference in the results may be related to different particle distribution and processing method of the granite stone.
## 4 Conclusions
### Linearization of the Differential Equation and Solution  
In the microvalve under consideration, the radii are much larger than the vertical gap between the discs. Furthermore, we expect the flow to be rather creeping than turbulent. For example, a setting with \(r_{0}=1.1\) mm, \(r_{1}=2.6\) mm, \(h=25\) um and \(p_{0}=10\) kPa, leads to a maximum Reynold's number of about \(\text{Re}=0.32\) in our simulations. The factor in front of the non-linear term then becomes about 0.13, while at the same time \(\alpha\approx 295\) and \(\beta=44\). Thus, we can neglect the non-linear term, and we obtain:  
\[C^{\prime\prime}(z)=-\frac{\gamma}{\ln\frac{r_{1}}{r_{0}}}\Delta p, \tag{17}\]  
where the dimensionless constant \(\gamma=\frac{p_{0}h^{2}}{\mu v_{c}r_{0}}\). For high Reynold's numbers, this simplification would not be appropriate, as then the turbulent flow contributes significantly to the fluidic resistance.  
Equation (A14) can be integrated twice over the height of the channel between the discs to obtain a polynomial of second order with two constants of integration. These constants are determined by applying no-slip boundary conditions at the discs. The coordinate system is oriented in such a way that the discs are symmetrically placed above, and below the \(xy\)-plane, i.e., they are located at \(z=\pm\frac{1}{2}\) in our dimension-less formulation. We then obtain:  
\[C(z)=\frac{\gamma}{8\ln\frac{r_{1}}{r_{0}}}\Delta p\cdot\Big{(}1-4z^{2}\Big{)}\] (A15)  
and further for the dimension-less velocity (added asterisks to clearly distinguish between entities with and without dimensions):  
\[v_{r}^{*}(r^{*},z^{*})=\frac{p_{0}h^{2}}{8\mu v_{c}r_{0}}\frac{1}{\ln\frac{r_{ 1}}{r_{0}}}\frac{\Delta p^{*}\cdot\big{(}1-4z^{*2}\big{)}}{r^{*}},\] (A16)  
and finally for the radial velocity:  
\[v_{r}(r,z)=\frac{1}{8\mu\ln\frac{r_{1}}{r_{0}}}\frac{\Delta p}{r}\Big{(}h^{2} -4z^{2}\Big{)}.\] (A17)
## 4 Results and Discussion
### Dense Image Matching
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Sensor Type** & **No. of GCPs/CPs** & \(\mu\) & \(\sigma\) & **RMSE** \\ \hline Pleiades & 43 GCPs & 0.07 & 0.28 & 0.29 \\  & 50 CPs & 0.07 & 0.30 & 0.31 \\ \hline WorldView-3 & 22 GCPs & 0.03 & 0.18 & 0.12 \\  & 50 CPs & 0.01 & 0.13 & 0.13 \\ \hline \hline \end{tabular} \(\mu\) and \(\sigma\) are the mean and standard deviations. All values are given in meters.  
\end{table} 
Table 4: Vertical accuracy assessment of Pleiades and WorldView-3 tri-stereo digital surface models (DSMs).
# A Novel Scheme for MIMO-SAR Systems Using Rotational Orbital Angular Momentum
## 4 Results  
In this section, we present some experiments to verify our proposed scheme at the proof-of-concept level. RDE experiments, referred to as single-in-single-out (SISO) and multiple-in-single-out (MISO) were carried out. The prototype of the transmitting antenna platform, which can transmit the rotational OAM beams, is shown in Figure 5. The OAM beams were generated by putting a spiral phase plate  
Figure 4: Processing flowchart of the OAM-based MIMO-SAR data.  
(SPP) ahead of a horn antenna with 20 dB gain [22]. In our experiments, two SPPs were used, i.e., mode \(+1\) and mode \(-1\). Before the experiments, the radiation pattern of the transmitting antenna was measured to make sure that they could generate vortex EM waves of correct OAM modes. The electrical machinery was used to rotate the SPP mechanically, and the rotational speed could be adjusted by the controller. Without changing the polarization, the rotational OAM beams could be generated by the platform.