esa-sceva/satcom-chunk-collection huggingface dataset:
# HiGoReg: A Hierarchical Grouping Strategy for Point Cloud Registration
## 4 Results
### Real-World Datasets
#### 4.2.2 Computational Efficiency  
In terms of computational efficiency, for the WHU-TLS subway dataset under a voxel size of 0.03 m, the batch solution required 454.66 s, whereas HiGoReg completed the registration in just 19.08 s under optimal grouping, approximately 4% of the batch runtime. At a voxel size of 0.05 m, the batch method took 71.93 s, while HiGoReg reduced this to 6.61 s, representing less than 10% of the original time. These results highlight the significant impact of high-dimensional matrix operations on computational cost in large-scale point cloud processing. As illustrated in Figure 10, similar to the simulation experiments, runtime was strongly influenced by the number of groups. When the data was divided into two groups, a noticeable improvement in efficiency was observed. Runtime continued to decrease until it reached a minimum at the optimal grouping configuration: 20 groups for the 0.03 m voxel case and 10 groups for the 0.05 m case. Beyond these points, increasing the number of groups led to longer runtimes due to overhead from excessive partitioning.  
For the statue dataset (Table 5 and Figure 12), HiGoReg also demonstrated superior efficiency under optimal grouping. Compared to the average runtime of the batch solution, HiGoReg achieved a reduction of 13.69% under equal weighting and 29.65% under nominal accuracy weighting. Regarding the stochastic models, the equal weighting approach was significantly faster, primarily because inverting the identity matrix was computationally trivial. In contrast, nominal accuracy weighting required the inversion of a non-trivial covariance matrix, which incurred additional computational overhead.
# The Design of a Long-Distance Signal Transmission System in a Bistatic RCS Testing System
## 2 System Principle and Simulation
### Selection of an Electro-Optic Modulator
The output of the modulator in this operating mode can be represented as follows:  
\[E_{out}(t)=\frac{\alpha}{2}E_{in}(t)\left[\exp\left(j\pi\frac{V\cos(\omega_{s} t+\theta_{s})+V_{DC}}{2V_{\pi}}\right)+\exp\left(-j\pi\frac{V\cos(\omega_{s}t+ \theta_{s})+V_{DC}}{2V_{\pi}}\right)\right] \tag{3}\]  
in which \(E_{in}(t)\) represents the optical carrier signal input to the MZM, \(\alpha\) denotes the insertion loss of the MZM, \(V_{\pi}\) is the half-wave voltage of the modulator, and \(V_{s},\omega_{s},\theta_{s}\) represent the amplitude, angular frequency, and initial phase of the modulating signal \(V(t)\), respectively. \(V_{DC}\) represents the DC bias voltage applied to the upper and lower arms. Figure 4: A schematic diagram of the MZM.
###### Abstract  
The current and torque ripple of inverter-fed induction motor drives is an inherent problem of control strategies working with switching frequencies in the range of multiple kilohertz, such as direct torque and, more recently, predictive torque control. If the drive operates in a wide-speed and wide-torque range and is equipped with a machine with an accessible terminal block whose winding is nominally connected in delta, then the current and torque ripple can be reduced by utilizing the delta-star winding changeover technique. When the winding configuration is switched from delta to star, the instantaneous motor phase voltage peak is lowered, and its total harmonic distortion is reduced. However, the control strategy must be adjusted according to the actual winding topology, mainly due to the difference in the coordinate transformations of the measured currents and the difference between the phase voltage vectors obtained from the inverter. This paper proposes a predictive torque control of an induction motor drive with a switchable delta-star winding configuration. The paper is supported by theoretical background, and the key idea is verified by simulations in MATLAB/Simulink and experiments conducted on a dSPACE-controlled 5.5-kW laboratory drive. The simulations validated the presented equations and show the effects of not respecting the actual winding topology. The experiments mainly focused on analyzing the total harmonic distortion of the currents and consumed electrical power in multiple operating points.  
Keywords:induction motor drive; delta-connected winding; predictive torque control; current ripple minimization +
Footnote †: journal: _Applied Sciences_
## 2 Materials and Methods
### Characterization of GaMBN  
The surface ions and surface morphology of GaMBN were observed via energy-dispersive X-ray spectroscopy (EDX) using a field emission scanning electron microscope (FESEM; MIRA3, TESCAN, Czech Republic). The composition of the sample was analyzed using X-ray diffraction spectroscopy (XRD; Rigaku, Tokyo, JAPAN) at 40 kV and 40 mA with CuK\(\alpha\) radiation (20 = 10-45\({}^{\circ}\)) and attenuated total reflectance-Fourier transformation infrared spectroscopy (FT-IR; Spectrum GX, PerkinElmer, Shelton, CT, USA). Surface area and pore size were determined by measuring N\({}_{2}\) adsorption-desorption isotherms and Brunauer-Emmett-Teller (BET) surface areas using an adsorption analyzer (Autosorb-iQ MP, Quantachrome instruments, Boynton Beach, FL, USA) at 77.35 K.
# MPC and PSO Based Control Methodology for Path Tracking of 4 WS4 WD Vehicles
## 6 Conclusions  
This paper presented two control methodologies applicable to four wheel steering and four wheel drive vehicle systems to track paths accurately. The system model is a nonlinear coupled dynamic model that is over-actuated. The first methodology determines the drive force inputs and steer inputs using an MPC based method coupled with a control allocation based on SQP. The second methodology is proposed as a fully optimization based method that is developed by refining a previously proposed PSO based method. The performance of the MPC-SQP method has been compared with the PSO based control method and a kinematic model based control method. In the simulation, the path tracking results have proved the superior performance of the MPC-SQP based controller. In the cases when computing times are considered, the PSO based controller offers more efficiency and better stability in computing compared with MPC-SQP based controller.  
Conceptualization, Q.T. and J.K.; Methodology, Q.T. and P.D.; Writing--Original Draft Preparation, Q.T. and Z.Z.; Writing--Review & Editing, J.K.; Supervision, J.K.; Project Administration, J.K.; Funding Acquisition, Q.T.  
This research was funded by the Fundamental Research Funds for the Central Universities, Grant No. 2017 JBM051 and 2015 JBC022, and the China Postdoctoral Science Foundation, Grant No. 2016M600910.  
This work was carried out at the School of Mechanical and Manufacturing Engineering, the University of New South Wales, Sydney, Australia.  
The authors declare no conflict of interest. The founding sponsors had no role in the writing of the manuscript.
# Assessment of Catalyst Selectivity in Carbon-Nanotube Silylesterification
###### Abstract  
The functionalization of carbon nanotubes (CNTs) plays a key role in their solubilization and compatibility for many applications. Among the many possible ways to functionalize CNTs, the creation of an Si-O-C bond is crucial for the formation of silicone composites. Catalyst-mediated silylesterification is useful in creating Si-O-C bonds because it is cost-effective and uses a hydrosilane precursor of lower reactivity than that of chlorosilane. However, it was previously demonstrated that two important silylesterification catalysts (zinc chloride and Karstedt's catalyst) exhibit different selectivity for oxidized functional groups that are present on the surface of CNTs after oxidative acid treatment. This report details the selective modification of CNTs with various oxygenated functional groups (aromatic and nonaromatic alcohols, carboxylic acids, ethers, and ketones) using diazonium chemistry. Modified CNTs were used to assess the specifity of zinc chloride and Karstedt's catalyst for oxygenated functional groups during a silylesterification reaction. [PERSON]'s catalyst appeared to be widely applicable, allowing for the silylesterification of all of the aforementioned oxygenated functional groups. However, it showed lower efficacy for ethers and ketones. By contrast, zinc chloride was found to be very specific for nonaromatic carboxylic acids. This study also examined the Hansen solubility parameters of modified CNTs.  
carbon nanotubes; aryl diazonium salts; silylesterification; hydrosilanes; zinc chloride; [PERSON]'s catalyst; Hansen solubility parameters. +
Footnote †: journal: Applied Sciences
###### Abstract  
To solve the problems with the existing active fault-tolerant control system, which does not consider the cooperative control of the drive system and steering system or accurately relies on the vehicle model when one or more motors fail, a multi-input and multi-output model-free adaptive active fault-tolerant control method for four-wheel independently driven electric vehicles is proposed. The method, which only uses the input/output data of the vehicle in the control system design, is based on a new dynamic linearization technique with a pseudo-partial derivative, aimed at solving the complex and nonlinear issues of the vehicle model. The desired control objectives can be achieved by the coordinated adaptive fault-tolerant control of the drive and steering systems under different failure conditions of the drive system. The error convergence and input-output boundedness of the control system are proven by means of stability analysis. Finally, simulations and further experiments are carried out to validate the effectiveness and real-time response of the fault-tolerant system in different driving scenarios. The results demonstrate that our proposed approach can maintain the longitudinal speed error (within 3%) and lateral stability, thereby improving the safety of the vehicles.  
Keywords:four-wheel independently driven; multi-input and multi-output; fault-tolerant control; drive system +
Footnote †: journal: Applied Sciences
## 3 Results
### Comparison with the Results of Previous Experiments  
The results of a previous study on leak detection, carried out with a similar experimental setup and test conditions [19], referred to as Exp-0, are reported here for comparison of the detection performance. Therein, leak detection could be achieved by using a scalar index, referred to as _Monitoring Index_ (MI), based on the standard deviation of vibro-acoustic signals (see Reference [7] for the analytical definition). The sensitivity to the leak was evaluated through a parameter referred to as _Monitoring Index Efficiency_ (MIE), defined as the ratio of the MI in leaking condition to the MI in non-leaking state, hence being conceptually analogous to the \(K_{R}\) ratio. Detection was considered as achieved for MIE  
Figure 11: \(K_{R}\) ratio as function of the acquisition duration for Hyd signals: (**a**) Test-1; (**b**) Test-2.  
Figure 10: \(K_{R}\) ratio as function of the acquisition duration for Aax signals: (**a**) Test-1; (**b**) Test-2.  
Figure 9: \(K_{R}\) ratio as function of the acquisition duration for Ard signals: (**a**) Test-1; (**b**) Test-2.  
values greater than 1.5 (which was arbitrarily chosen as a reasonable threshold), while sensitivity to the leak was deemed satisfactory for MIE values greater than 2. Moreover, the performance could be significantly enhanced by filtering the measured signals with band-pass filters. The MIE values obtained in Reference [19] for a 100-600 Hz passband are reported in Table 2.  
In Exp-0, the hydrophone (Hyd) provided remarkably good results, where it showed a very high sensitivity to all the leaks. The accelerometers were not capable of detecting the farthest leak (i.e., L3), but had proved effective for detecting leaks L1 and L2. In particular, sensor Ard had exhibited a sufficient sensitivity, whereas the performance of sensor Aax was significantly superior.  
A comparison between the \(K_{R}\) ratio values of Test-1 and Test-2, and the MIE values of Exp-0 shows that for the Aax sensor, the new method based on the \(K_{R}\) can apparently provide a sizeable enhancement of the leak detection performance, due to the almost doubling of sensitivity to both leaks L1 and L2. Conversely, the hydrophone was revealed as neither adequately sensitive nor sufficiently reliable with the new method. Regarding sensor Ard, an increased sensitivity (more than +150% with respect to Exp-0) was be observed for Test-2, in which the leaks L1 and L2 were correctly detected. Hence, the use of radial vibration signals with the new detection method may be still viable, in case its robustness can be improved.
# SNR-Based Receiver-Type Decision Using Deep Learning for Multiple-Input Multiple-Output Detection
## 5 Conclusions  
In this paper, we proposed the MIMO receiver based on deep learning that alternates the receiver type between linear and nonlinear receivers to achieve low computational complexity while maintaining nearly optimal error performance. For this purpose, the proposed receiver established a threshold, and the DNN selected the appropriate receiver type, either the ZF or ML receiver, based on the characteristics of the channel. In the simulation results, we have shown that the proposed receiver achieves nearly identical performance to that of the conventional ML receiver while offering reduced complexity.  
As already explained, there is a limitation that the prediction of the channel conditions is performed only for the receiver-type decision. Moreover, the threshold for the receiver-type decision is determined heuristically. Applying the proposed method to a general number of antennas is challenging with the current heuristic approach, as parameter optimization is critical for practical implementation. Therefore, we will extend our work to design a deep learning-based receiver structure for channel prediction and detection in massive MIMO systems, focusing on optimizing the parameters of the receiver.  
Conceptualization, D.S.; methodology, S.L. and D.S.; validation, S.L.; formal analysis, S.L. and D.S.; writing--original draft preparation, S.L.; and writing--review and editing supervision, D.S. All authors have read and agreed to the published version of the manuscript.  
This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (No. 2020R1A6A1A12047945).  
My manuscript has no associated data and materials.  
Author [PERSON] was employed by the company Samsung Electronics Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
# Surface Discharge Mechanism on Epoxy Resin in Electronegative Gases and Its Application
## 1 Introduction
In this paper, we analyze the effect of SF\({}_{6}\) and O\({}_{2}\) in compressed gas on electron generation during the surface discharge progress, and provide useful physical information for the surface insulation design of high-pressure SF\({}_{6}\)-free high-voltage equipment. This study describes the surface discharge characteristics of epoxy resin in compressed gases (i.e., SF\({}_{6}\), dry air, and N\({}_{2}\)) under a non-uniform electric field. It aims to understand the solid-gas composite insulation characteristics and analyze the effect of secondary electron attachment emitted from the dielectric surface on the surface insulation performance. The reason for the excellent surface insulation performance of electronegative gases (SF\({}_{6}\) and dry air) is explained in detail in this paper, based on the physics governing the gas discharge and the surface discharge mechanisms. The remainder of this paper is organized as follows. The experimental setup and experimental procedure are introduced in Section 2. The experimental results of the surface discharge characteristics in compressed gas dielectrics are presented in Section 3. The surface discharge mechanism and the insulation design method of an SF\({}_{6}\)-alternative insulating gas, based on the effect of the electronegative gases and electron swarm parameters, are discussed in Section 4. Finally, conclusions are presented in Section 5.
## 3 Experimental Results
### Compressive Strength  
Figure 4a shows the compressive strength test results. For Qu0, Qu7.5, and Qu15, the 1-day compressive strength values are 13.6, 11.84, and 10.81 MPa, respectively, and from Qu0 to Qu15, at 1 day, the reduction in compressive strength is about 20%. The compressive strengths at 28 days are 54.82, 46.11, and 41.55 MPa, respectively. Compared with 1 day, the compressive strength at 28 days decreases more obviously.  
As cement hydration proceeds, hydration heat is released. Hydration products fill pore spaces, and strength increases. Hence, hydration heat is closely related to strength development. Figure 4b shows the relationship between the measurement results for hydration heat and compressive strength at 1, 3, and 7 days. Overall, there is an exponential function relationship between the two results. In this test, the compressive strength unit is MPa and the hydration heat unit is J.
## 7 Simulation and Evaluation
### Block Generation Time  
We then compare the generation time of blocks without partitioning and after partitioning, as shown in Figure 9. When the number of users processed by a single satellite is 4 per second, the time of block generation is 0.122 s without regional division and 0.053 s after regional division, which reduces the time consumed by 56%. In the case of no regional division, the calculation amount of the primary node is 5 times that after regional division. As the number of users increases, the time of verifying transactions on the primary node keeps increasing. Meanwhile, the ratio of time shortening increases with the increase in the number of users. With 32 users, the time after partition shortens by 74%.
## 5 Results
### Combined Results  
The first part of the questionnaire collected user information. Besides the gender or origin background, which was primary focused for the previous results analysis, Sections 5.2-5.7, there are more settings which might influence the color preference level. Since the Chinese participants were the bigger group with 161 subjects, relations between participant's age and time of the day were investigated within this group only. Statistical tests were performed using the Mann-Whitney-U procedure, asymptotic \(p\) and the significance level \(\alpha=0.05\). The results are displayed in Figure 11, for age dependency in a and time of the day dependency in b.  
Figure 10: Word cloud results displayed for Q1 as “Which light system do you want to have in your future vehicle?” in (**a,b**). For Q2 as “If you don’t like your current interior lighting in your vehicle, which proposals you have to improve it?” in (**c,d**). Results are separated by genders globally. Amount \(n\) of participants for each question: (**a**) male answers with \(n=59\); (**b**) female answers with \(n=47\); (**c**) male answers with \(n=36\); (**d**) female answers \(n=25\).  
Significant differences were observed within the Chinese age settings: blue and purple were less age-dependent, other monochromatic colors might have a more attractive function for younger male and multichromatic ones might be more related to younger female Chinese participants. Effect power \(r\) indicated a weak to medium size with \(r\) between 0.23 and 0.38. Within the time of the day, more Chinese participants selected as their preferred colors multichromatic ones in the evening time for autonomous driving. For manual driving, no significances were found. Effect power \(r\) shows a weaker distribution within 0.20.  
Significant differences within all participants globally regarding the weather settings were also identified, as shown in Figure 12a. Cyan and blue colors were more selected during no-sunshine settings compared to sunny days, with a weak effect size of \(r\) around 0.14-0.23. Last, there was a considerable support for in-vehicle lighting identified within all participants globally. In Figure 12b, 79% of all participants wanted to have an interior lighting system in their new vehicle as presented in this online survey. Most of them already in moderate vehicle price classes. Detailed statistics for the combined results are added in the Supplementary Materials of this study, Section S3, Tables S13-S15.  
Figure 11: Within the Chinese participants only: (**a**) age and light color preferences; (**b**) time of the day and color selection dependencies; including statistical evaluations with significances \(p<0.05\) marked with \({}^{*}\) or for \(p\leq 0.06\) marked with (\({}^{*}\)).  
Figure 12: (**a**) Global relations between weather and color preferences; (**b**) expected vehicle price with in-vehicle lighting options. Statistical evaluations with significances \(p<0.05\) marked with \({}^{*}\).
## 3 Temperature-Based ET Models: Advantages, Drawbacks, and Evolution of Research
### Single-Source Surface Energy Balance Models
#### 3.1.5 Mapping Evapotranspirationpiration at High Resolution with Internalized Calibration (METRIC)  
METRIC is a model that estimates ET based on the surface energy balance. It uses short-wave and long-wave data from satellite images, digital elevation models, and ground-based weather data, eliminating the need for precise surface temperature measurements. METRIC internally calibrates the surface energy balance using ground-based reference ET, aligning with traditional ET methods and reducing computational biases. The model is flexible, does not require knowledge of crop types or growth stages, and can detect reduced ET due to water scarcity. METRIC's calibration compensates for regional advection effects, making it suitable for arid and semi-arid regions [54].  
Recent research validates METRIC's accuracy based on lysimeter measurements, achieving 10% daily ET estimation on a sub-field scale, particularly in semi-arid regions. Sensitivity analysis identifies influential parameters, suggesting the need to refine equations related to these variables for enhanced accuracy [55].  
The calibration of satellite-based energy-balance algorithms for ET estimation is challenging, and the CIMEC process, standing for calibration using inverse modeling at extreme conditions, addresses this by utilizing extreme conditions for calibration. A statistics-basedprocedure simplifies the calibration process by using the relationship between vegetation amount and surface temperature. This approach improves accuracy, especially for inexperienced operators [56].  
Comparing 8-bit and 12-bit resolution imagery from Landsat-8, it is found that using 8-bit thermal data does not significantly affect ET retrievals in METRIC. Differences in signal-to-noise ratio and scaling between images from different missions have minimal impact on ET determination. Recalibration of Landsat-8 thermal data does not affect the accuracy of ET retrievals in METRIC due to the model's compensation for biases [57].  
To simplify the model and reduce computational requirements, a simplified version of METRIC called S-METRIC was proposed by [58]. S-METRIC offers a faster and simpler approach with comparable performance to METRIC in estimating monthly ET values using relatively limited input data.  
SWH-METRIC was introduced by [59] as a combined model that facilitates the challenging task of continuous daily ET estimation at a fine spatiotemporal scale. The results demonstrated a noteworthy alignment between the estimations by the SWH--METRIC model and the measurements through the eddy covariance technique. Moving towards hybrid models might have the potential to bridge existing gaps and enhance the overall accuracy of ET estimation.