esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Laboratory and DEM Modelling Establishment
### DEM Modelling Establishment  
PFC (Particle Flow Code) (Version 6.0 used in this study) is a DEM simulation analysis software program developed by Itsaca, a company in the United States. In this software, the smallest units of the simulated object are circular particles (2D) or spheres (3D), and the particles (or spheres) are connected to each other through contacts [40]. Contacts can transmit forces and moments, and are updated and calculated at each timestep [40]. Therefore, PFC software can be used to simulate the complex mechanical behaviour of granular materials or blocks, including particle flow, breakage, deformation, and other large deformation issues [41; 42; 43]. However, due to the mechanical calculations and updates of tens of thousands of particles and contacts at each timestep, the computational efficiency and accuracy significantly increase with the increase in particle numbers. For complex models, modelling and computational time and accuracy have become its inevitable shortcomings. However, for rock or rock mass simulation tests, while ensuring the size effect, the number of particles can be controlled within an effective range. Therefore, PFC software has been proven to be an effective means of numerically simulating rock mechanics [15; 22; 27; 28; 41; 42; 43]. It can be seen from Figure 3a that the design of the on-site rock mass and indoor experiment has certain planar problem characteristics because the interface between the rock slab and the dangerous rock mass only has changes in two directions. In light of this, the three-dimensional characteristics of the interface roughness can be simplified into a planar problem. Considering the calculation speed and accuracy, the 2D version of the PFC software (PFC2D) was chosen for numerical simulations in this study. It is important to ensure that the dimensions of the simulated samples align precisely with those of the laboratory test specimens, as depicted in Figure 4a. The samples were established using a shear box genesis approach [25]. Particles were generated within the upper plate and the rock slabs of the lower plate, thereby maintaining the structural integrity and independence of each component. The particle radius in the simulation varies, with the maximum being 1.05 mm and the minimum 0.7 mm, resulting in a total of 13,812 particles that constitute the sample. As shown in Figure 4b, the simulation loading methodology involves the application of shear stress through the movement of the lower wall from left to right. The movement velocity of the walls is set to 0.05 m/s. Under this velocity, the calculation timestep is automatically set to 2.01 \(\times\) 10\({}^{-7}\) s/step. It needs 0.995 \(\times\) 10\({}^{5}\) steps to move 1 mm. Referring to the related study results in reference [44], this loading velocity adheres to the quasi-static requirements necessary for the experimental testing.  
Figure 4: Numerical model establishment and loading methods: (**a**) Model establishment; (**b**) Loading methods.
# Binary PSO with Classification Trees Algorithm for Enhancing Power Efficiency in 5G Networks
## 6 Conclusions  
Minimizing the power consumption of the SCs and elevating the PE of the network are huge challenges facing the 5G HetNets. In this paper, to tackle these challenges, novel algorithms are proposed based on linear increasing IW-BPSO and SFR. The BPSO algorithm is used for SC on/off switching reducing the power consumption of the system without deteriorating the QoS of the UEs. Moreover, the linearly increasing IW is exploited to enhance the convergence of the BPSO algorithm to find the minimum number of active SCs. Furthermore, the CT-based SFR is proposed, where the SCs are divided into center and edge regions and different sub-bands are allocated to the edge regions of the adjoining SCs, minimizing the interference among the SCs. The results demonstrate that the proposed algorithms surpass the other conventional algorithms with regard to the total system power consumption, the total system throughput, the PE, and the outage probability. Additional work can be done in the future to address the coverage hole problem in Voronoi cells and to enhance the accuracy of the PSO algorithm using dynamic inertia weight.  
Conceptualization, M.O., B.A. and S.E.R.; methodology, M.O., B.A. and S.E.R.; software M.O.; writing--original draft preparation, M.O.; writing--review and editing, B.A. and S.E.R.; All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The authors declare no conflict of interest.  
Figure 10: Outage probability for various SINR thresholds in the case of 900 UEs.
## 3 Innovative SHM Techniques
### Image and Computer-Vision Based Approach
#### 3.2.3 Infrared Thermography  
Infrared thermography (IRT) is another well-established imaging approach, which has been applied for over 40 years for historical building diagnostics [173] and has grown considerably in recent years, with increasingly advanced applications and with development in terms of image post-processing. An IR scanner or camera can detect thermal radiation emitted by surfaces (e.g., walls, floors), which is then converted into a visible image representing their temperature contour map. Thanks to surface temperature differences, the technique may help detect hidden physical characteristics typical of historical structures, such as discontinuities, cavities, inclusions, or embedded elements [174], as well as moisture, capillary rise, and heat leaks [175].  
[PERSON] et al. [176] presented the results of applying IR thermography to investigate the structural damage of the Church of Santa Maria ad Cryptlas (XIII century) hit by the L'Aquila earthquake in 2009. In particular, the results were compared with those obtained from a pre-earthquake thermographic campaign conducted in 2007. It was found that some damages caused by the earthquake corresponded to thermal anomalies previously detected in the IRT of 2007, confirming the effectiveness of thermography as a preventive diagnosis and monitoring tool.  
IRT techniques can be combined with other non-destructive techniques to achieve more comprehensive and complete data to assess the conservation state of the analysed structures [155,177]. [PERSON] et al. [177] combined TLS and IRT to investigate the conservation of an ancient monumental compound in southern Italy. Different measurement surveys were conducted over one year. The main findings were that the combination of data provided by both TLS and IR thermography allowed for the identification of anomalies in the masonry structures (cracks, detachments, moisture zones) and the presence of different construction materials (corresponding to different phases of rebuilding and restoration). The authors concluded that applying these combined methods could be used to monitor the progression of decay in ancient buildings over time due to permanent loads and accidental events, such as earthquakes.  
More recently, [PERSON] et al. [155] investigated the state of conservation of a historical Roman masonry bridge in Italy using UAV 3D photogrammetry, IRT, and ground penetration radar. The results demonstrated how the synergetic use of these contactless non-destructive diagnostic tools can provide precious information about the state of structural health and guide the design of restoration interventions in the context of preventive conservation of architectural heritage. In particular, IRT results corroborated the hypothesis that the actual degradation condition of the bridge was mainly caused by water retention within its materials.
## 2 Literature Review
### Stream Data Classification  
There are many constraints that must be taken into account when mining streaming data: (1) the impossibility of storing data samples due to their infinite arrival; (2) real-time processing is required due to the rapid arrival of data samples; and (3) the possibility of changing items' distributions, which may require altering the current structure of the classification model [22; 23].  
Concept drift means that the data being collected may change from time to time, each time based on a certain minimum persistence. There are two important issues related to change: the cause of the change and the speed of the change [24]. ADWIN (Adaptive Sliding Window) is an estimation technique designed to detect changes in a data stream based on a sliding window with an adaptive size. In this technique, as long as the average value in the window does not change, the length of the window will not be updated [23; 24].
# Rician Beamforming: Despeckle Method via Coarray Projection Stochastic Analysis
## 6 Discussion  
One of the most disturbing phenomena affecting ultrasonic image quality is nonuniformity of noise variance along the inspection area. This compromises CAD tasks and image readability. The proposed method mitigates this phenomenon from two different perspectives:  
* Contrast improvement. RiB improves image contrast without affecting texture. Compared with standard phantom data, contrast values obtained from RiB are consistent.
* Tissue interface sharpness. RiB notably improves tissue interface contrast, especially in the case of tissue-cavity interfaces, in particle-free cavities.  
Results obtained by means of RiB beamforming can be fed to further denoising systems, highly improving results. In this paper, pdf usage has been restricted to a single point evaluation related to DAS value. Point-wise, RiB estimations could be combined with alternative sources of information to produce enhanced images (fusion), easier to interpret.  
Robust mean and variance estimations are obtained with this method, thanks to diversity principle, applied to coarray projection. Estimations can be used to implement new image domain despeckle methods that exploit noise variance variability. Such information is instrumental to more complex denoise filtering methods, and also could be used in other medical imaging areas, such as Magnetic Resonance Imaging (MRI). Though it is out of the scope of this contribution to formulate this kind of filtering processes, there is increasing interest among the scientific community in applying these methods to tissue medical imaging.  
Conceptualisation: [PERSON] and [PERSON]; data curation: M.P.R.; formal analysis: [PERSON]-[PERSON]; funding acquisition: [PERSON]-[PERSON]; investigation: A.I.R.; methodology: [PERSON]-[PERSON]; project Administration: [PERSON]-[PERSON]; resources: A.I.R. and M.P.R.; software: [PERSON]-[PERSON], M.P.R.; supervision: [PERSON]; validation: A.I.R.; visualisation: [PERSON]-[PERSON]; writing--original draft: [PERSON]; writing--review & editing: [PERSON]. All authors have read and agreed to the published version of the manuscript.  
This research was funded by AEI/FEDER UE, grant number DPI2016-80239-R.  
The authors declare no conflicts 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.  
The following abbreviations are used in this manuscript:  
\begin{tabular}{l l} BW & Bandwidth \\ CAD & Computer Aided Detection \\ DAS & Delay and Sum Beamformer \\ FMC & Full Matrix Capture \\ IQR & Interquartile Range \\ MIMO & Multiple-Input and Multiple-Output \\ MRI & Magnetic Resonance Imaging \\ NDT & Non-Destructive Testing \\ NLmeans & Non Local Means based Filtering \\ pdf & Probability Density Function \\ RiB & Rician Beamformer \\ RF & Radio Frequency \\ ROI & Region of Interest \\ SAFT & Synthetic Aperture Focusing Technique \\ SNR & Signal to Noise Ratio \\ TFM & Total Focusing Method \\ ULA & Uniform Linear Array \\ \end{tabular}
# An Adaptive 24 GHz PSO-Based Optimized VCO in Next-Generation Wireless Sensor Networks
## 5 Conclusions  
This paper presented an adaptive PSO approach for optimizing a 24 GHz VCO in next-generation wireless sensor networks, particularly for self-driving vehicle radar systems.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Corners** & **FF** & **\% Change FF** & **TT** & **SS** & **\% Change SS** \\ \hline Frequency (GHz) & 24.25 & 0.1 & 24.2 & 24.1 & 0.41 \\ Power consumption (mW) & 1.48 & 11.5 & 1.35 & 1.52 & 12.6 \\ \hline \hline \end{tabular}
\end{table}
Table 4: PVT variation simulation results.  
Figure 17: Phase noise histogram.  
The proposed adaptive PSO algorithm enhances the optimization process by reducing the number of calculations while improving efficiency in complex engineering problems. The performance evaluation using benchmark functions demonstrated the effectiveness of the adaptive PSO in achieving faster convergence and better optimization results. The VCO using an adaptive PSO resulted in significant improvements, achieving a low phase noise of \(-120\) dBc/Hz at a \(1\) MHz offset, a wide tuning range of \(21.2\%\), and ultra-low-power consumption of only \(1.35\) mW at \(0.9\) V. In our work, a comparative analysis with traditional PSO techniques further validated the superiority of the proposed method in optimizing the VCO for automotive radar applications. The results show that adaptive PSO-based optimization is an effective method for improving the performance of radar systems in self-driving vehicles. Future work may explore extending this method to other RF circuit designs to further optimize next-generation wireless communication systems. Additionally, integrating machine learning techniques with an adaptive PSO could further improve optimization efficiency by dynamically adjusting algorithm parameters based on real-time feedback. Finally, exploring the potential of this optimization approach in emerging technologies, such as 6G communication systems and Internet of Things (IoT) applications, could pave the way for more efficient and scalable RF circuit designs.  
Conceptualization, K.T., U.A. and T.S.D.; methodology, K.T., U.A., T.S.D. and Y.L.; validation, M.N.A., J.-Y.R. and B.-S.K.; formal analysis, K.T., U.A. and T.S.D.; investigation, K.T. and U.A.; resources, Y.L., J.-Y.R. and B.-S.K.; writing--original draft preparation, K.T., U.A. and T.S.D.; writing--review editing, M.N.A., Y.L., J.-Y.R. and B.-S.K.; supervision, Y.L., J.-Y.R. and B.-S.K.; funding acquisition, Y.L., J.-Y.R. and B.-S.K. All authors have read and agreed to the published version of the manuscript.  
The authors acknowledge funding from the National Research Foundation (NRF) of Korea through the BK21 FOUR Project (Smart Robot Convergence and Application Education Research Center) (Grant Number: 2018R1D1A1B07043286)  
Not applicable.  
Data Availability Statement: Data are contained within the article.  
The authors declare no conflicts of interest.
## 5 Performance Assessment of BDS-3 Satellite Clocks
### Results
Figure 12: Overall atomic clock performance for different types of GNSS satellites, including the frequency accuracy, drift rate, and stability. In terms of the stability with the averaging time of 86,400 s, the range of BDS-3 RAFS satellites is 0.2\(\sim\)1 \(\times\) 10\({}^{-14}\) with an average value of \(8.64\times 10^{-15}\), which is worse than the stability of GPS satellites with an average value of \(4.52\times 10^{-15}\) and variation range of 3\(-6\times 10^{-15}\). The stability of GPS is comparable to the result of [34] with an average value of \(5\times 10\)-15. The variation range of 86,400 s stability for BDS-3 PHM satellites is 3-7 \(\times\) 10\({}^{-15}\) and the average value is \(5.28\times 10^{-15}\), which is slightly better than the average value of \(5.57\times 10^{-15}\) for Galileo satellites with the range of 0.2\(\sim\)1 \(\times\) 10\({}^{-14}\). The stability of BDS-2 GEO, IGSO, and MEO satellites is \(3.72\times 10^{-14}\), \(2.40\times 10^{-14}\), and \(2.08\times 10^{-14}\), respectively, which is comparable to the results of [34].
# Study on the Effectiveness of Multi-Dimensional Approaches to Urban Flood Risk Assessment
## 2 Methodology
### Exposure
#### 2.4.2 Underground Risk by Flood Depth  
The severity of flood damage can differ depending on whether underground structures are present. To evaluate the extent of damage based on flood depth, an underground weight factor is employed, which is calculated using a flow rate formula that estimates floodwater inflow at various depths. Specifically, this factor is determined by comparing the volume of floodwater flowing into underground facilities--derived from the above-ground flood depth--with the total volume of the underground space. The formula used to calculate floodwater inflow into underground facilities is shown below (Ministry of the Interior and Safety [26]).  
\[Q_{t}=1.59L_{w}h_{t}^{1.65} \tag{1}\]  
\[\gamma_{t}^{id_{b}}=\frac{Q_{t}}{\forall_{0.3}^{id_{b}}} \tag{2}\]  
where \(\forall_{0.3}\) represents the flood volume when the water depth is 0.3 m in the underground space, \(\gamma\) refers to the underground risk rate, \(Q\) is the inflow volume into the underground space, \(L_{w}\) represents the inflow width (1.2 m), \(id_{b}\) represents the unique identifier for each building (\(b\)), and \(h_{t}\) denotes the above-ground water depth at time \(t\). Under the Enforcement Rules of the Act on Guarantee of Convenience Promotion for Persons with Disabilities from the Ministry of Health and Welfare, the minimum effective doorway width is set at 0.9 m. However, in this study, \(L_{w}\) has been adjusted to 1.2 m to provide additional clearance, a width commonly observed in typical doors. Furthermore, while door operation generally becomes impossible at a water depth of 35 cm, a more conservative threshold of 30 cm has been adopted to account for potential difficulties in operation. ([PERSON] [27])
###### Abstract  
Rootstocks are widely used in viticulture due to their resistance to biotic and abiotic stress. Additionally, rootstocks can affect vine growth and berry quality. This study evaluated the effects of eight rootstocks (101-14, 110R, 5A, 5 BB, Ganzin 1, Harmony, Riparia Gloire, and SO4) on the vine growth, berry ripening, and flavonoids and aromatic profiles of Cabernet Sauvignon in two consecutive seasons (2015-2016). With few exceptions, minor differences were observed among grafted and own-rooted vines. Own-rooted vines produced the least pruning weight but the highest yield. 101-14, 5 BB, and SO4 slightly reduced total soluble solids, but increased acidity, showing tendencies for retarding maturation. Ganzin 1 inhibited the accumulation of flavan-3-ols in berry skins. Furthermore, concentrations and proportions of epicatechin-3-O-galate were decreased by rootstocks, except for 110R. 5A, Harmony, and Riparia Gloire enhanced flavonoid concentrations. SO4 slightly decreased most of the individual anthocyanin concentrations. With respect to volatile compounds, 110R, Riparia Gloire, and SO4 induced reductions in concentrations of total esters, whilst 101-14, Ganzin 1, 110R, and 5 BB led to increases in the concentrations of C\({}_{13}\)-norisoprenoids. Therefore, with respect to the negative effects of SO4 on berry ripening and the accumulation of anthocyanin and volatile esters, SO4 is not recommended in practice.  
Cabernet Sauvignon; rootstock; graft; vine growth; ripening; flavonoids; volatile compounds 1
# Occlusion-Robust Multi-Target Tracking and Segmentation Framework with Mask Enhancement
## 3 Methodology
### Mask-Conditioned Feature Fusion Network  
Traditional feature extractors perform poorly when processing occlusion and acquiring temporal information. Therefore, we proposed a mask-conditional feature fusion network to solve the limitations. The network integrated a mask-guided attention mechanism and a spatial-temporal feature aggregation sub-network so as to improve tracking robustness in crowded scenes. Its main sub-modules aew shown in Figure 1 below.
# Time Domain Investigation of Hybrid Intelligent Controllers Fed Five-Phase PMBLDC Motor Drive
###### Abstract
The fault tolerance capability of multiphase motors has been discussed in [28], and various speed controller techniques applied to three-phase PMBLDC motors have been discussed in [29; 30; 31; 32]. After going through all of the above literature, it is understood that the time domain analysis of five-phase PMBLDC motors with multiple speed controllers has not been discussed by researchers. Moreover, the testing of the dynamic and steady state performance of BLDC motor drives for electric vehicle applications has been restricted to three-phase machines in the literature under no load and load conditions [33; 34; 35; 36; 37; 38; 39; 40; 41]. There has been no similar work carried out for multi-phase/five-phase BLDC motors so far. Hence, the proposed work carried out in this paper uses different load conditions applied to different controller-fed drives, and their performance characteristics are discussed. In this context, the design and performance evaluation of conventional and intelligent controllers are analyzed and compared for five-phase PMBLDC motor drives in terms of time domain specifications under different load conditions in this paper, as shown in Figure 1. The simulation results show that the ANFIS controller-based five-phase PMBLDC motor drive system has the benefits of low torque ripples, a high starting torque, a better transient response along with negligible overshoot, and a smaller rise and settling time, which make it ideally suited for electric vehicle applications. The rest of this paper is organized as follows: Section 2 describes the mathematical model of five-phase PMBLDC motor drives. Section 3 describes the design aspects of different controllers for the modeled drive. Section 4 explains the simulation of the drive with step and linear load variations. The experimental setup and corresponding results are described in Section 5. The conclusions of this paper are given in Section 6.