esa-sceva/satcom-chunk-collection huggingface dataset:
# Linear Approximation Signal Detection Scheme in MIMO-OFDM Systems
## 2 System Model  
In this system model, the MIMO-OFDM system has \(N\) transmit antennas and receive antennas. Also, it is assumed that \(N=2^{P}(P\geq 2)\) is considered where \(P\) is natural number, which is larger than one. At the MIMO-OFDM transmitter, an input data is demultiplexed into \(N\) data substreams. Then, \(N\) data substreams go through digital modulation, inverse fast Fourier transform (IFFT) for multi-carrier transmission. Finally, guard interval (GI) is added to reduce the effect of inter-symbol interference (ISI) and inter carrier interference (ICI). At the receiver, \(N\times 1\) MIMO received vector \(\mathbf{Y}\) is as follows,  
\[\mathbf{Y}=\mathbf{H}\mathbf{X}+\mathbf{Z}, \tag{1}\]  
where \(\mathbf{H}\) is \(N\times N\) rich scattering complex Rayleigh flat fading channel matrix, \(\mathbf{X}\) is \(N\times 1\) transmit vector, and finally, \(\mathbf{Z}\) is \(N\times 1\) zero mean additive white Gaussian noise vector. The channel matrix \(\mathbf{H}\) is represented as follows,  
\[\mathbf{H}=\left[\begin{array}{cccc}H_{11}&H_{12}&\cdots&H_{1N}\\ H_{21}&H_{22}&\cdots&H_{2N}\\ \vdots&\vdots&\ddots&\vdots\\ H_{N1}&H_{N2}&\cdots&H_{NN}\\ \end{array}\right], \tag{2}\]  
where an element \(H_{ij},\ i,\ j=1,2,\ldots,N\) denotes channel coefficient from the \(j\)-th transmit antenna to the \(i\)-th receive antenna. Also, each \(H_{ij},\ i,\ j=1,2,\ldots,N\) is independent and identically distributed (i.i.d) random variables.
# Earth Rotation Parameters Estimation Using GPS and SLR Measurements to Multiple LEO Satellites
## 3 ERP Estimation Based on the Single LEO Satellite
### ERP Estimation with Different LEO Satellites
In order to explain this phenomenon, here we give Figure 6, which shows the percentage of observations from core stations and non-core stations for LAGEOS satellites, and the number of core stations and non-core stations. We can see that the non-core stations account for a large part of the stations tracking LAGEOS, but only contribute to about 30% of SLR observations to LAGEOS. The small amount of observations for non-core stations weaken the solution strength for the station coordinates, and lead to a degraded positioning accuracy for non-core stations. This may explain the larger average RMS values with an IQR of nearly 25 mm for the E, N, and U components for all the stations. For the core stations, LAGEOS and some LEO solutions can achieve a comparable positioning accuracy, and the GRACE-C and GRACE-D solutions even present a smaller RMS value in the up component, with an IQR decrease of nearly 4 mm. These analyses suggest that it is tenable to achieve a desirable station coordinate result based on the LEO orbit of high accuracy.
## 1 Introduction
In addition to nonlinear disturbance observers, a Linear Extended State Observer (LESO) is a form of linear disturbance observer that has the advantage of tuning [25; 26; 27; 28]. The feedforward control technique also plays an important role in control engineering as a useful and classical disturbance-compensation method, as it can compensate for measurable disturbance as part of control engineering. [PERSON] designed an adaptive feedforward compensation controller to improve disturbance-rejection and tracking performance for jumping disturbances and large noises [29]. [PERSON] designed and implemented a discrete time-tracking controller for a precision positioning table actuated by direct-drive motors for which the existing disturbance-observer design techniques were extended to account for time delay in an industrial plant, and it performs well in practical scenarios [30]. In this paper, we propose a novel type of NQTAUV by simplifying the LESO design to one parameter and integrating a control scheme that compensates for unmeasurable underwater disturbances. We propose a nonlinear controller and an LESO with a single tuning parameter for attitude tracking the hover and transition modes, and these lead to simplicity in controller design, tuning, and implementation. The NQTAUV encounters various disturbances. During transition mode, the rotors tilt from \(0^{\circ}\) to \(60^{\circ}\), and the tilt process results in disturbance torque. As speed increases, hydrodynamic force and torque play an important role as disturbance to the body of the vehicle [31]. The proposed LESO estimates the disturbance, changing from the nonlinear system to the nominal system without disturbance, and the nonlinear controller was designed to stabilize the nominal system. This article is structured as follows. Section 2 introduces the attitude system model of the NQTAUV, where the attitude is presented based on the Rodrigues parameters, and the error model of the attitude-tracking system is then established. In Section 3, a disturbance rejection scheme is proposed that contains an LESO and a controller, which was designed to track the target attitude under disturbances, and the stability of the entire system is analyzed. In Section 4, three typical experiments validate the performance of the proposed scheme by comparing the attitude stabilization of the hover mode, the attitude tracking of the hover mode, and the attitude stabilization of the transition mode, both with the LESO on and with the LESO off.
# Fault Diagnosis of Wind Turbine Planetary Gear Based on a Digital Twin
## 3 Fault Diagnosis Method Based on Digital Twinning
### Establishment of Fault Diagnosis Model  
#### 3.1.1 Feature Extraction Using Empirical Mode Decomposition  
The EMD algorithm was proposed by [PERSON] [27]. It can decompose the signal according to the time scale characteristics of the data without any basis function and has a high signal-to-noise ratio. Therefore, the EMD method is used in this paper. According to the strain signal's energy characteristic information, the component's energy entropy is decomposed to realize the selection of characteristic parameters, as shown in Figure 7.  
First, the eigenmode function (IMF) is obtained after EMD decomposition, and the energy entropy of each IMF component is calculated [28]. Then, the feature vector is selected. The frequencies of different-order IMF components differ, and the higher the IMF  
Figure 6: Intelligent diagnosis process for planetary gear of wind turbine.  
Figure 7: Recognition process of feature extractor based on IMF energy.  
order, the fewer high-frequency components it contains, as shown in Figure 8. Therefore, the IMF energy entropy of orders 1-5 is selected to design the classifier to improve feature vector extraction. The steps are as follows:  
1. The signal is decomposed by EMD to obtain the IMF components \(c_{i}=(t)\).
2. The lines are summarized, and the energy entropy of each IMF \(E_{i}=(t)\) is calculated: \[E_{i}=\int\lvert c_{i}=(t)\rvert^{2}dt\] (1)
3. The energy proportion of each IMF is obtained and normalized: \[p_{i}(t)=\frac{E_{i}(t)}{\sum_{i=1}^{n}E_{i}(t)}(i=1,2,\ldots,n)\] (2)
4. The IMF energy entropy is defined as: \[H=-\sum_{i=1}^{n}p_{i}\log p_{i}\] (3)
## 5 Conclusions  
The observed runoff was obtained by drainage data from the Wanyan River pumping station, and the theoretical runoff was calculated using the surface runoff calculation method based on the rainfall and land use data. Based on the theoretical runoff, the drainage coefficient was calculated using the empirical formula and the average draining formula. The main conclusions were as follows.  
1. As rainfall and rainfall duration increased, both the observed runoff and the theoretical runoff increased. The observed runoff was typically less than the theoretical runoff due to the limitation of the pumping capacity and the high water levels in the Heilongjiang River and Songhua River. The drainage coefficient calculated by theoretical runoff showed that the design flow of the Wanyan River pumping station could not meet the drainage demand under 5-year return period rainfall.
2. When the 1-day rainfall greater than the 3-year return period was discharged in 2 days, the results of the average draining formula were greater than those of the empirical formula, and the T\({}_{\rm E}\) was greater than the design drainage duration. In this condition, it was safer to use the average draining formula to calculate the drainage coefficient for drainage engineering design. Under the 1-day rainfall duration with a 3-year return period and discharging 3-day rainfall in 4 days, the results of the empirical formula were greater than those of the average draining formula, and the design drainage duration was greater than T\({}_{\rm E}\). In this condition, it was safer to use the empirical formula to calculate the drainage coefficient. Therefore, when calculating the drainage coefficient, a longer drainage duration could be selected for places with good water storage conditions.
3. F\({}_{\rm A}\) ranged from 173 to 2029 km\({}^{2}\) for 1-day rainfall duration and from 5353 to 55,883 km\({}^{2}\) for 3-day rainfall duration. F\({}_{\rm A}\) increased with the increase in rainfall duration and decreased with the increase in return period. When the rainfall duration and drainage duration were long, the calculation results of the average draining formula were much smaller, which was unsafe for engineering design.  
Conceptualization, S.W.; methodology, L.Y., S.W., Y.T. and Y.L.; validation, S.W., Y.T. and Y.L.; formal analysis, S.W., Y.T. and Y.L.; investigation, L.Y., Y.L. and Y.T.; data curation, L.Y. and Y.L.; writing--original draft preparation, L.Y., Y.T. and Y.L.; writing--review and editing, L.Y., Y.T.; project administration, S.W.; funding acquisition, S.W. All authors have read and agreed to the published version of the manuscript.  
This work was funded by the National Natural Science Foundation Program of China (No. 52079145, No. 51779274).  
Not applicable.
## 2 Experimental Setup
### Fuels and Tracers Investigated  
In accordance with our previous studies [1; 32; 33; 36] and to avoid composition variations of commercial gasoline, we used the well-defined two-component surrogate fuel Toliso (65 vol. % isooctane, 35 vol. % toluene) instead. The sooting tendency of commercial gasoline was mainly driven by its aromatic components, such as toluene, benzene or xylene, which were in sum up to 35% in total volume of gasoline. Toluene is known as an octane number enhancer, and gasoline contains up to 15 vol. % of this component [37]. Toliso has thermo-physical properties similar to those of multi-component gasoline, and toluene mixtures with isooctane (or n-heptane) lead to a similar sooting behavior as commercial gasoline [38]. The effect of biofuel admixture on the LIF and Mie signals was considered by blending Toliso with 20 vol. % of ethanol (E20). The chemical and physical properties of the investigated fuels and conventional gasoline for various ambient conditions are shown in Table 1.  
The dye nile red (Sigma-Aldrich) was used for all investigations. It belongs to the group of fluorophores and its aromatic ring structure contains polar substituents. Its properties lead to a high sensitivity to the chemical and physical environment of surrounding solvent molecules [39]. For the preliminary characterization of the spectral emission of the fuel-dye mixture in a dye cell, the selected concentration of nile red was 9.38 mg/L [28]. This relatively low concentration prevents measurement uncertainties caused by excessive extinction effects due to the long probe path in the dye cell (in comparison to the droplet diameter). To achieve a good signal-to-noise ratio in the 2D droplet investigations, the fuel was doped with 100 mg/L nile red concentration.
## 4 Discussion
### Comparison of Perceived Exertion Rating across Conditions  
The results of the RPE assessments revealed that the intensity of the perceptual responses differed between the test conditions. Participants perceived a low effort during the _neutral_ performance of the plank. However, the reported exertion was higher only by modifying the head position from _neutral_ to _flexion_, showing a significant variation of 1.53 points in the OMNI-RES scale, according to the sEMG response. Interestingly, despite the no change in sEMG activity, the perceived level of effort had a significant increase of 1.30 points when switching from _neutral_ to _extension_. However, no differences were found in the perceived effort between _flexion_ and _extension_, although there were significant differences in sEMG activity. Exertion rating has previously been used as an indicator of exercise intensity and neuromuscular fatigue of the core muscles for this stabilisation bridge exercise [40; 41]. Related studies have reported how different pelvic and scapular positions, as well as the performance of specific lumbar stabilisation manoeuvres, can modulate participants' exertion rating and intensify perceived neuromuscular fatigue when the plank differs from traditional performance [36; 39]. In this sense, our findings would seem to corroborate the fact that perceived neuromuscular fatigue is affected when the plank differs from typical performance by showing how participants rated the highest levels of exertion when the cranio-cervical segment was modified from the natural alignment of the cervical spine, increasing their perceived effort regardless of core muscle activation.
# Cycle Consistent Generative Motion Artifact Correction in Coronary Computed Tomography Angiography
## 3 Methodology  
Our proposed pipeline aims to enhance a motion-affected 3D CT volume and generate a motion-corrected version using neural networks. Therefore, we adhere to the following methodology:  
1. We extract image patches along the artery centerline. These patches are aligned with their corresponding target motion-free phase patch using Dynamic Time Warping (DTW). DTW is an algorithm used to match correspondences between pixels across the sequence of patches. This ensures that the corresponding patch pairs exhibit similar anatomical features. This alignment is essential to ensure the accuracy and reliability of the subsequent steps in the process;
2. Utilizing the patch corresponding to slower motion as the target, we employ a style transfer network to produce a synthetic ground truth image (SynGT) for the motion-perturbed image. Style transfer is performed between pairs of corresponding patches in different phases in a 4D CT and alters only the style (local texture), not the content(structure). Our assumption is that motion artifacts are closer to style and thus can be reduced using this process;
3. A CycleGAN network is trained to perform motion compensation, with the input consisting of pairs of motion-affected and SynGT patches;
4. Motion-corrected patches are reinserted and interpolated into the original 3D CT volume to compensate for the motion artifacts of the mid RCA.  
Figure 2 illustrates a schematic representation of the training processes mentioned in the second and third points. The subsequent sections explain the technical details of each subprocess.
## 3 Nonthermal Methods  
Thermal sterilization is widely used due to its efficiency, low cost, and universal applicability, but it can also affect the sensory and nutritional quality of food. For this  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Method** & **Description** & **Product** & **Reference** \\ \hline Sterilization & Conventional method: Packaging is undertaken before heat treatment. The processing is usually carried out at 105-110 \({}^{\circ}\)C / 30–45 min. & & \\ Sterilization & UHT or aseptic method: Packaging is undertaken after heat treatment. For the ultra-high temperature and short time (UHST) and very high temperature and short time (UHST), the processing is at 135–150 \({}^{\circ}\)C/1–20 s & & [35, 36] \\ \hline Refrigeration & Artificial cooling of foods to temperatures below their freezing point & & \\  & Basic requirement for the processing and storage of milk and milk products is low temperature in the cold storage depending on the type of product to be stored. For & milk & [40, 41] \\  & example, milk is stored at 3–4 \({}^{\circ}\)C & & \\ \hline  & 2–8 \({}^{\circ}\)C & & cheese & [42] \\ \hline  & Artificial cooling of food to temperatures at which a sufficient amount of water & & \\  & solidifies, stopping the activity of microorganisms & ice cream & [43] \\  & Ice cream is stored at –30 \({}^{\circ}\)C. & & \\ \hline Freezing & & skimmed milk & \\  & Freeze & skimmed powder & \\  & concentration & & \\  & & beverages & \\  & & probiotic fresh cheese & \\  & & whey protein & \\  & & ice cream & \\ \hline \hline \end{tabular}
\end{table}
Table 1: \(Cont.\)reason, nonthermal sterilization technologies have been developed, such as chemical sterilization, irradiation, high hydrostatic pressure, and high-intensity ultrasound. These nonthermal methods offer advantages in preserving food quality but come with challenges, such as high equipment costs and health risks.
## 3 Estimation Algorithm
### Combined SR-CKF and SVSF
To address discrepancies between the constant and time-varying smoothing boundaries and ensure filter stability, the SVSF is utilized when the time-varying boundary extends beyond the constant one. The state trajectory of the CSVSF considering the influence of disturbances is shown in Figure 1.
# HYPSO-1 CubeSat: First Images and In-Orbit Characterization
## 3 In-Orbit Payload Performance
### Spatial Resolution
#### 3.1.1 Ground Resolvable Distance (GRD)
The standard deviations are higher than the 0.2-0.4 pixels typically found in satellite imagery. The resolution in worse-performing bands is beyond three pixels in terms of LSF FWHM. Super-resolution methods and panchromatic sharpening that leverage the sharpest wavelengths could be used to improve the resolution of the higher and lower wavelength bands. Investigation of potential venues for image enhancements is a topic for future research [39].
# Extensible Hook System for Rendezvous and Docking of a CubeSat Swarm +
## 4 Simulation results
### CubeSat Trajectory Tracking  
During this simulation, the objective was to measure the required forces and energy to perform a maneuver that would place the CubeSat in a particular pose. The simulation was configured to move the CubeSat from \((0,0,0,0,0,0)\) to (25 m, 25 m, \(-10\) m, \(\pi/8\) rad, \(-\pi/4\) rad, \(\pi/8\) rad) in \((X,Y,Z,\alpha,\beta,\gamma)\) position and orientation coordinates, traversing a distance of 36.7523 m in 500 s. Figure 5 shows the obtained results, where the displacement required a maximum longitudinal force of 100 mN on the Y axis, and a maximum torque of 1.385 for a rotation on the Y axis. Moreover, the motion required a total energy of (4.3296 Ns, 4.3248 Ns, 1.7377 Ns) for X, Y, and Z.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline Total mass (w/o EHS) & 27.7 kg \\ \hline EHS mass & 2.41 kg \\ \hline CubeSat size & 246.3 \(\times\) 246.3 \(\times\) 454 mm (16U) \\ \hline EHS size (folded) & 122.51 \(\times\) 444.54 \(\times\) 200 mm (4U) \\ \hline EHS max. distance & 5026 mm \\ \hline EHS links & 24 \\ \hline EHS joint friction & 0.01 N s/m \\ \hline CubeSat longitudinal max. force & 0.1 N \\ \hline CubeSat max. torque & 0.2 Nm \\ \hline EHS link max. force & 20 N \\ \hline EHS joint max. torque & 200 mNm \\ \hline \hline \end{tabular}
\end{table}
Table 1: CubeSat parameters during simulation.
## 1 Introduction  
The absorption of ultraviolet-visible (UV-Visible) light by condensed phase dielectric materials generally results in the promotion of ions, atoms, molecules or chromophores to short-lived electronic excited states. In optically pure media that lack effective channels for complete energy dissipation, a degree of fluorescence will commonly ensue--yet the site of fluorescent emission will often differ from the site of initial excitation. In the short time interval between the photon absorption and emission events, single- or multi-step electronic energy transfer (EET) of the excitation may occur between proximal particles. Over short, sub-wavelength ranges, each such transfer step takes the form of a radiationless pairwise interaction, typically between electronically distinct particles. One of the particles (the excited particle, the initial absorber) acts as the energy donor, the other as an acceptor [1, 2, 3, 4, 5, 6].  
Recently it has been shown that, fundamentally, the same mechanism also operates in atom physics, where photoexcitation of a donor atom leads to indirect ionisation of a nearby acceptor [11, 12]. Here, too, the associated pairwise energy transfer can still be described in the same way as transfer between molecules or chromophores, based on a description cast in terms of quantised field interactions. There is, nonetheless, an important difference: in suitably complex, heterogeneous condensed phase media, multi-step resonance energy transfer may arise, usually exhibiting a spectroscopic gradient. This signifies that a small amount of energy is commonly lost through vibrational relaxation after each transfer step, which means that back transfer from each acceptor to its energy donor becomes exceptionally inefficient [13]. Similar effects can be observed in quantum dot systems [14, 15, 16, 17, 18].  
An essential feature of EET (also known as resonance energy transfer, RET) is that the process occurs spontaneously, by engaging quanta of the vacuum field [19]. However, it has been shown that its efficiency and rate are amenable to modification by a variety of means [20; 21; 22; 23; 24; 25; 26; 27], including local media effects and externally applied static electric or electromagnetic fields. In this paper, a comprehensive quantum electrodynamical framework is described in sufficient detail to explain the mechanism of inter-particle coupling in EET, providing a basis for theory that represents these more complex energy transfer systems. Adapting Feynman diagram methods, we establish results that exhibit fundamental connections between all these effects, also eliciting their detailed dependence on parameters that are under experimental control.
# A Fair Cooperative MAC Protocol in IEEE 802.11 WLAN
## 1 Introduction  
Cooperative communications have emerged as a promising solution to some existing challenges for wireless networks. Cooperative communications provide performance improvement by exploiting a new paradigm beyond the conventional point-to-point and point-to-multipoint communication models. The broadcast nature of a wireless channel results in the overhearing of packets by the middle nodes between source and destination nodes. These middle nodes (relay or helper) can perform the forwarding when their participation leads to performance improvement. The capabilities of cooperative communications attract different wireless technologies and different OSI layers. The special features of IEEE 802.11 medium access control (MAC), integrated in cooperative schemes, have led the research community to provide a diversified set of solutions for different challenges, from rate adaptation techniques at the physical layer to service differentiation at the application layer and even cross-layer approaches [1; 2; 3; 4; 5].  
To achieve the objectives of cooperative IEEE 802.11 MAC protocols, the relay selection mechanism is very important. The relay selection mechanism impacts on different aspects of network performance, such as spectrum efficiency, reliability, quality of service, energy efficiency, and fairness. In this paper, we propose a new cooperative protocol in IEEE 802.11 MAC which improves the network performance in terms of throughput, lifetime, and time fairness.  
The rest of the paper is organized as follows: Section 2 discusses the state of the art of existing cooperative protocols. The proposed relay selection algorithm is described in Section 3. In Sections 4 and 5, we present performance analysis and simulation results of our proposed algorithm respectively. Section 6 concludes the paper and presents future directions for research.