esa-sceva/satcom-chunk-collection huggingface dataset:
# Distributed Resources Allocation Method for Space-Ground Integrated Mobile Communication System
## 3 System Model
### User Request Procedure  
To illustrate the network access process, we take one MS (\(K_{2N}\)) as an example, using the architecture in Figures 1 and 2.  
Firstly, the core network controller sends the pre-trained model with the real-time crowd state to all the physical network carriers, and then these nodes send the model to the \(K_{2N}\) after secondary training.  
Secondly, \(K_{2N}\) in the certain area \(M_{2}\) ask for a connection to send messages through the network. Here, the message will be analyzed by the designed algorithm to give it a classification of service type and allocated data rate at the same time. Also, \(K_{2N}\) gets its location (i.e., longitude, dimension and altitude) from the HEO navigation satellite as other parameters.  
Thirdly, the algorithm embedded in MS will use these parameters to calculate the most suitable RB requirement with transmitting power. Then, \(K_{2N}\) will employ the DP-DQN model to decide which physical network (e.g., Satellite Network eMBB Slice) to switch in. Here, for \(K_{2N}\) which is located in the near-urban area, the slices allocated from the satellite will be much more expensive than those from the cellular network.  
Finally, the analysis result (service type, access network and needed RB number) will be sent to a particular network. Available slice blocks will then be allocated to the user to meet the demand of data rate. If the current network no longer has enough resources due to resource requests from other users, the core network will meet its needs as far as possible according to the principle of proximity. If this is still not satisfied (in practice, such a scenario is very rare), feedback will be sent to the mobile station to recalculate the appropriate access network.
# Analysis of the Influencing Factors of Grinding Uniformity under Three-Body Coupling Grinding Mode
## 4 Effects of Ball-Billet and Grinding Disc Slip on Rotating Angular Velocity
### Relative Sliding between theBall-Billet and the Outer Disc  
This study sets the sliding between the ball-billet and the outer disc only. In other words, \(V_{A}=V_{C}=0\) and \(V_{B}\
eq 0\). Similarly, the relation between \(\Omega_{b}/\Omega_{C}=0\) and \(N_{t}\), as well as that between \(\theta\) and \(N_{t}\), can be deduced from Equation (2), as shown in Equations (8) and (9).  
\[\frac{\Omega_{b}}{\Omega_{C}}=\frac{R_{B}N_{t}(1-S_{B})+R_{C}}{2R_{A}(1+\sin \alpha)} \tag{8}\]  
\[\tan\theta=\frac{1-S_{B}}{\frac{R_{C}}{R_{B}N_{t}}+(1-S_{B})}\left(\frac{1+ \sin\alpha}{\cos\alpha}\right)\times 2-\frac{1+\sin\alpha}{\cos\alpha} \tag{9}\]  
where \(S_{B}=\frac{V_{B}}{R_{B}\Omega_{B}}\) is the sliding-friction ratio between the ball-billet and the outer disc. The structural parameters in Table 2 were brought into Equations (8) and (9). Based on calculation results, Figure 8 can be plotted.  
Similar to the analys is in the above section, the following conclusions are drawn:  
1. With the increase in the sliding-friction ratio between the ball-billet and the outer disc (\(S_{B}\)), the slope of the relation curve between \(\Omega_{b}/\Omega_{C}\) and \(N_{t}\) decreases gradually. However, the intersection point between the relation curve and the \(y\)-axis is kept constant under different \(S_{B}\). When \(S_{B}=0\), \(\Omega_{b}/\Omega_{C}\) is a constant value. When \(S_{B}\
eq 0\), \(\Omega_{b}/\Omega_{C}\) increases with the increase in \(N_{t}\). This result demonstrates that when the rotating speed of the inner disc is constant, the revolving angular speed (\(\Omega_{b}\)) of the ball-billet may also increase with the increase in \(N_{t}\). The variation of the revolving speed of the ball-billet is intensified with the decrease in \(S_{B}\);
2. With the reduction in \(S_{B}\), the ball-billet can realize the variation of rotating angular velocity within \([-90^{\circ},90^{\circ}]\) in the relatively small variation range of \(N_{t}\). When complete slippage occurs between the ball and the outer disc (\(S_{B}=1\)), the motion state of the ball-billet is completely determined by the inner disc, and \(\theta\) is a constant value.  
Based on the above analysis, the relative sliding behavior of the ball-billet with inner and outer discs have similar influences on the motion state of the ball-billet. Given that the slippage between the ball-billet and grinding discs has direct influences on the variations of the rotating angular velocity, revolving speed, and other kinetic parameters, it influences the distribution of the grinding tracks on the spherical surface directly. Such influencing degree can be analyzed by the sliding-friction ratio between the ball-billet and the grinding discs.
# Real-Time Mitigation of the Mobility Effect for IEEE 802.15.4g SUN MR-OFDM
## 3 Related Works
### Overview of CFO Estimation Technologies  
Due to the effect of CFO on the channel estimation, CFO estimation is a very important factor in the OFDM systems design and optimization. Many researchers have focused on finding the CFO estimation methods. The CFO can be estimated in two ways: the time-domain estimation techniques (or pre-FFT synchronization) and frequency-domain estimation techniques (or post-FFT synchronization). Pre-FFT synchronization is the estimation performed before the OFDM demodulation (FFT processing). The advantage of the pre-FFT approach is that it requires less estimation time and less computing power because the FFT process is not needed. Pre-FFT synchronization can be divided into two categories: data-aided (DA) and non-data-aided (NDA) [11; 12]. The DA methods [13; 14] insert a known OFDM training symbol into the start of every OFDM packet for the purpose of FFO estimation. The disadvantage of these approaches is that they reduce the data transmission efficiency because the training symbols need to be inserted in the OFDM packet in exchange for a CFO estimation range wider than the NDA algorithms [-1, +1] [15]. The NDA methods use the CP part to estimate the fractional CFO [16; 17]. They take advantage of the correlation of the CP and the corresponding OFDM symbol part to estimate the FFO. However, this method can only estimate the CFO in the range of [-0.5, +0.5] [18], but it does not need additional OFDM training symbols, which improves the data transmission efficiency. Post-FFT synchronization is the estimation method performed after the FFT processing. This method takes advantage of the correlation between the received pilot subcarriers and a shifted version of the known pilot subcarriers [19] to estimate the CFO. Depending on the spacing among pilot subcarriers, the CFO range up to multiple integers can be estimated. Usually, post-FFT synchronization is employed for the IFO left estimation after pre-FFT synchronization. We chose the appropriate approach depending on the specifications and the system requirements.
###### Abstract  
The main principles of hydroabrasive wear of parts of the pumping stages of well's electric submersible pumps are considered in this article. The concentration, grain-size distribution and shape of solid particles have the greatest impact on the abrasion ability of particles of mechanical impurities interacting with the parts of pumping equipment. The implementation of filters is the most effective and affordable way to protect borehole electric submersible pumps from hydroabrasive wear. Filters reduce the concentration and decrease the average grain-size of mechanical impurities going through the pumping stages. The authors propose variants of constructive and schematic solutions of self-cleaning slot filters, providing an increase in the operating time of electric centrifugal pump units during production of well fluid with a high content of mechanical impurities. The operating principle of the proposed filters is described. The results of calculations of deformation of tubing string during the increase in pressure at the oil wellhead are presented, confirming the possibility of restoring the permeability of spring filter elements without lifting the pump unit to the surface.  
electric submersible pump unit (ESP); borehole oil production; mechanical impurities; hydroabrasive wear; self-cleaning filter; increased time between failures +
Footnote †: journal: Applied Sciences  
Acticle  
Increasing the Time between Failures of Electric Submersible Pumps for Oil Production with High Content of Mechanical Impurities  
Appl. Sci. 20221264  
Previous research [7; 9; 10; 11; 12; 13; 14] is devoted to improving the reliability of ESP pumping liquid with a high content of mechanical impurities. These studies have considered technical means of increasing the resistance of working stages of pumps to hydroabrasive wear, i.e., changes in the design of working stages and use of wear-resistant materials. It is noted that these methods are often characterized by a decrease in the energy efficiency of operation and an increase in the cost of pumps, and do not always provide a significant increase in the operating time of ESP installations in difficult operating conditions.  
In works [14; 15; 16; 17], the results of investigations into the process of filter functioning, when using ESP as a part of submersible units, are presented. A common disadvantage of the existing designs of downhole and ESP inlet filters is their low dirt capacity.  
The main regularities of the process of hydroabrasive wear of working stages of downhole ESP are described in the present article. The designs of prospective ESP filters are presented and their permeability restoration (cleaning of filter elements) under well conditions without lifting the units to the surface is described.
# Electrons and X-rays to Muon Pairs (EXMP)
## 3 \(e^{-}-\gamma\) Collider Scenarios
### High Efficiency Hard X-ray FELs  
The photon beam needed to achieve ultra high luminosity in the \(e^{-}-\gamma\) collider is unique: it must carry an outstanding number of photons per pulse at the same repetition rate of the primary electron beam. It must also match the ultra tight focus spot size at the collision of the primary electron beam, set by its very short beta function value at the focus (hundreds of microns), in the range of a few tens of nanometers. The only radiation source capable of meeting these demanding requirements is an FEL driven by a dedicated ERL, and operated in SASE mode with tapering, as illustrated in reference [13]. Efficiency in the range of a few percent is achievable, to a number of photons per pulse, as listed in Table 1, according to photon energy. The partial coherence of the amplified FEL radiation also makes it possible to focus its photon beam down to nanometer spot sizes, as discussed in reference [14]. This is the second crucial property of FELs that makes it possible to foresee a luminosity for the \(e^{-}-\gamma\) collider scenarios of up to \(2\times(2.5-12.5)\times 10^{41}\) cm\({}^{-2}\)s\({}^{-1}\). The FEL beams considered in this study carry an impressive amount of photon beam power: running at 800 MHz in CW mode, the photon number per second exceeds \(10^{21}\). With photon energies in the range of tens to hundreds of keV, that means up to 100 MW of radiation beam power. Since the FEL efficiency, considering the special mode of FEL operation as illustrated in reference [13], is about 1%, the power carried by the electron beam driving the FEL must be of the order of 100 MW/0.01 = 10 GW, as listed in Table 1.  
There are two main challenges on the FEL side: (a) focusing FEL beams down to 10 nm was demonstrated at about 10 keV of photon energy, while EXMP needs at least 60 keV of FEL photons, and (b) handling FEL beams at a very large average power likely implies splitting the photon beam by means of multiplexing on different beam lines, which are further taken to the interaction point with the electron beam from different polar angles. These issues need further studies and evaluations in order to design a feasible collision scenario.
# A Self-Diagnosis Method for Detecting UAV Cyber Attacks Based on Analysis of Parameter Changes
###### Abstract  
We consider how to protect Unmanned Aerial Vehicles (UAVs) from Global Positioning System (GPS) spoofing attacks to provide safe navigation. The Global Navigation Satellite System (GNSS) is widely used for locating drones and is by far the most popular navigation solution. This is because of the simplicity and relatively low cost of this technology, as well as the accuracy of the transmitted coordinates. Nevertheless, there are many security threats to GPS navigation. These are primarily related to the nature of the GPS signal, as an intruder can jam and spoof the GPS signal. We discuss methods of protection against this type of attack and have developed an experimental stand and conducted scenarios of attacks on a drone's GPS system. Data from the UAV's flight log were collected and analyzed in order to see the attack's impact on sensor readings. From this we identify a new method for detecting UAV anomalies by analyzing changes in internal parameters of the UAV. This self-diagnosis method allows a UAV to independently assess the presence of changes in its own subsystems indicative of cyber attacks.  
U  
A UAV; GPS; cyber threats; anomalies; spoofing; entropy; cyber attacks
## 4 Mesh Regularity: Geometric Quality and Gradient Reconstruction in MFAMs
### Geometric Mesh Quality  
The different possibilities offered by the previously described meshing algorithms and the fine tuning through manual corrections allow the user to iterate through MFAMs with increasingly better geometric quality properties. Nevertheless, high quality meshes will always be difficult to achieve due to the restriction of using isolines which are defined by the magnetic topology over arbitrary simulation domains, and thus requiring special attention to issues appearing close to the domain boundaries.  
Mesh geometric quality is described through the following set of element properties:  
Figure 9: Meshing examples obtained with two methods for an initial number of \(\lambda\) and \(\sigma\) isolines equal to 50: (**a**) Smoothing method; (**b**) Expanded Exponential Stretching method & manual correction.  
\[\begin{array}{l}smoothness=\frac{max(A_{detomat},A_{a_{a}a_{a}a_{a}})}{min(A_{ detomat},A_{a_{a}a})}\\ \\ aspect ratio=\frac{max(facet-length_{detomat})}{min(facet-length_{detomat})}\\ \\ skewness=max\left[\frac{\theta_{max}-\theta_{e}}{180^{\prime}-\theta_{e}},\frac{ \theta_{e}-\theta_{max}}{\theta_{e}}\right]\end{array} \tag{14}\]  
where \(A\) represents the areas, _element_ and _adjacent_ represent, respectively, the element being considered and the elements adjacent to it, \(\theta_{max}\) is the largest angle in the element polygon and \(\theta_{e}\) is the angle in an equiangular polygon with the same number of sides as the element considered. Large aspect ratios and smoothness may be intuitively understood to affect the interpolation of the solution and gradient reconstruction in the element faces (although this may be offset in part by using a weighted Least Squares (LSQR) method, see Section 4.2); skewness may be related to large errors for fluxes in facets which are nearly parallel and affect the cells in the boundary of the domain.  
In order to show how the functionality in the Mesh Generator allows one to improve the geometric quality of the MFAM, two different meshes are compared through their quality statistics: One generated using the smoothing method with no manual correction and one generated using the expanded-exponential-stretching method and then applying a manual correction of the mesh. The two meshes used are the ones presented in Figure 9. Figure 10 shows that better geometric quality properties are achieved through the implemented functionality. This better quality is shown by the decrease of the mean, maximum and accumulated values of the different parameters analyzed.  
Figure 10: Mesh quality for different meshing examples: (**a**) Aspect Ratios, (**b**) Smoothness, (**c**) Skewness; (top) 2D contours in the mesh and (bottom) Comparison for mesh quality statistics between Exponential-Stretching method mesh presented in Figure 9 and Smoothing method mesh. Different values (min., max., mean, most likely, 80% cumulative, 90% cumulative, 95% cumulative) are used for the evaluation.
## 2 Method Description
### Finding the Variation Law for Detached Chip Area  
As already mentioned in the previous section, there is a close link between the cutting force magnitude and the detached chip area. For simplicity, without any direct impact on the proposed method's effectiveness, we will further accept a proportional relation between them. Hereby, the shape of the cutting force variation law is similar to the shape of variation for the detached chip area.  
Given the periodicity of the process (except for tool engagement and disengagement phases) and due to the successive machining of consecutive teeth, it is sufficient to look for the variation law during (i) the tool engagement phase, (ii) the complete machining of a tooth, and (iii) the tool disengagement phase.  
Finding the variation law for detached chip area starts by determining the detached chip area for each increment of the toothing process, which corresponds to an increment of the rolling motion, respectively, to one kinematical cycle of the cutting motion. In order to do so, the next four-step algorithm must be followed:  
1. Firstly, the tool model is imported into the file which contains the workpiece model.
2. The toothing process is then simulated by giving each of the two items (the cutting tool and the workpiece) the motion corresponding to the one increment of the rolling motion, after which the two items are overlapped.
3. The option _Remove of Operation_ modeling tool [22] is subsequently applied; thus, one item is subtracted from the other, the result being a new item, which is the workpiece from which the common region (corresponding to the detached chip) was eliminated.
4. The detached chip area is, finally, calculated as the difference between the workpiece area that was measured before and after the intersection, by using the _Measure Item_ tool from the _Measure_ toolbar [22].  
Here, we must mention that the accuracy of the area measurement we thus achieved, if performed as suggested above, is \(10^{-3}\) mm\({}^{2}\).  
Since the next step requires an analytical expression of the variation law for the detached chip area \(A\), a function \(f\) approximating the series of areas calculated from the first up to the last contact point between the cutting tool and the worked piece has to be found. The _Curve Fitting_ toolbox of MatLab may be used, for example, for this purpose [24].  
As in all the gearing processes addressed here, the worked piece has rotational motion, and the position of the coupled cutting tool and worked piece will be defined by the angle \(\varphi\) made by the worked piece with a reference start position, corresponding to the first contact between the two elements (when \(\varphi=\varphi_{min}\)). Obviously, the maximum value \(\varphi_{max}\), corresponding to the last contact, depends on the actual conditions of a given process. Thus, it can be written as  
\[A(\varphi)\cong f(\varphi),\ \ \varphi\in[\varphi_{min}\ \dots\ \varphi_{max}]. \tag{1}\]
# Multivariate Time Series Data Prediction Based on ATT-LSTM Network
## 4 Experiment
### Dataset and Evaluation Indicators
#### 4.1.2 Model Evaluation Indicators  
We used Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) as the evaluation indicators of the model. At the same time, MAE and RMSE were also used as evaluation indicators for comparison experiments with other models. The calculation formulas of these two evaluation indicators are as follows:  
\[MAE=\frac{1}{N}{\sum\limits_{i=1}^{N}}{|y_{i}-x_{i}|} \tag{13}\]  
\[RMSE=\sqrt{\frac{1}{N}{\sum\limits_{i=1}^{N}}{(y_{i}-x_{i})^{2}}} \tag{14}\]  
where \(N\) represents the length of the test set, \(y_{i}\) represents the model's predicted value, and \(x_{i}\) represents the actual value.
# Electrically Tunable Propagation Properties of the Liquid Crystal-Filled Terahertz Fiber
## 3 Results and Discussion  
A full-vector FEM method [29; 30] was employed to investigate the PBGs and guided modes properties of the designed THz LC-MOF.
## 5 Conclusions  
In this study, the spatial and temporal variations in the NEP, WUE, and CUE in the MRYR, as well as the corresponding variations in meteorological factors, were estimated using the Geographic Information System (GIS), Google Earth Engine (GEE), and remote sensing (RS) techniques. The correlation between the NEP, WUE, and CUE of different vegetation types and meteorological factors, as well as the effects of land cover on carbon sinks, were emphasized. The main conclusions are as follows:  
1. Based on the changes in precipitation, temperature, ETa, PET, and DSI from 2001 to 2022, the drought trend in the MRYR is weakening, and climate change has been moving toward warming and humidification.
2. The NEP, WUE, and CUE generally showed an upward trend from 2001 to 2022, with annual mean values of 221.49 gCm\({}^{-2}\), 0.52 gC m\({}^{-2}\)mm\({}^{-1}\), and 0.31, respectively, and average growth rates of 7.75 gC m\({}^{-2}\)a\({}^{-1}\), 0.012 gC m\({}^{-2}\) mm\({}^{-1}\)a\({}^{-1}\), and 0.009 a\({}^{-1}\), respectively. Spatially, the fastest growth rate was observed in the more arid northwestern part of the MRYR. In contrast, the growth rate was lower in the southeastern region, where water resources are relatively abundant. Of the four vegetation types, the grassland NEP, WUE, and CUE had the highest growth rates, followed by cropland; however, in the forests and shrubs, the WUE and CUE growth rates tended to be close to 0 or less than 0.
3. An analysis of the standardized anomaly indices showed that precipitation accumulation contributed to the accumulation of carbon sinks. Among the three selected meteorological factors, the DSI had the highest correlation with the NEP, WUE, and CUE, and the correlation of precipitation with the NEP, WUE, and CUE showed latitudinal zonality. This suggests that precipitation is the main control factor affecting the water-carbon cycle in the region, not temperature.
4. From 2001 to 2022, a total of 67,671.27 km\({}^{2}\) of land cover types changed in the MRYR, and the regional NEP increased by 15.07 Tg. The interconversion between grassland, forest, and cropland accounted for 81.60% of the changed area.  
**Author Contributions:** Conceptualization, X.H. and B.Z.; methodology, X.H. and B.Z.; software, X.H. and Z.-L.S.; formal analysis, X.H., Q.-Q.H., and X.-Y.Z.; validation, X.H.; data curation, X.H. and H.Y.; visualization, X.H. and Q.-Q.H.; writing--original draft preparation, X.H.; writing--review and editing, B.Z.; funding acquisition, B.Z. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was funded by the National Natural Science Foundation of China (41561024).  
**Data Availability Statement:** No new data were created or analyzed in this study. Data sharing is not applicable to this article.  
**Acknowledgments:** Thanks to [PERSON] of Northwest Normal University for their constructive comments on this article.  
**Conflicts of Interest:** The authors declare no conflicts of interest.