esa-sceva/satcom-chunk-collection huggingface dataset:
# Real-Time 3D Reconstruction Pipeline for Room-Scale, Immersive, Medical Teleconsultation
## 3 Pipeline Overview
### Textured Rendering  
Our texturing method Figures 1 and 4) projects each fragment into the image space of the color cameras to gather the optimal pixel and into the depth cameras to check for  
Figure 3: Pipeline Overview. This figure shows the data flow of our reconstruction system. After temporal filtering, we generate an octree of all nonempty voxels, then surface samples and normals are found for each voxel. Simplification decimates octree nodes on flat surfaces. Finally, mesh extraction from the octree is performed using an adapted version of dual contouring for point clouds, and a GPU-based step called finalization performs quad-triangulation, filters duplicate triangles, and removes unused vertices.  
occlusion, like in shadow mapping. Since we generate a simplified mesh, choosing a camera per face causes more inconsistencies and discontinuities than dynamically choosing a camera per pixel (Figure 5). If multiple cameras see the same surface, a selection of strategies is available. One strategy, to maximize resolution, chooses the camera with the shortest distance to the observed surface. Since we record the physical shading observed at the color camera, another strategy can use the camera with the smallest viewing angle difference between the current eye position and physical camera to prioritize correct shading.
## 4 Results  
### Groundwater Chemistry  
The chemical characteristics of the groundwater in the studied aquifers are presented in Table 1. According to the results of the chemical analyses, the pH of Quaternary aquifer groundwater ranged from 6.8 to 8.6 with a median of 7.3, the pH of PNA samples ranged from 6.7 to 8.1 with a median of 7.2, and the pH of NSA samples ranged from 7.6 to 8.2 with a median of 7.9. The pH values reflect that most groundwater samples had neutral to slightly alkaline characteristics. Groundwater temperature mainly depends on the geothermal gradient and ambient temperature at the land surface [43]. The groundwater temperature in the Quaternary aquifer ranged from 21 to 32.3 \({}^{\circ}\)C, the PNA samples' temperatures ranged from 22.9 \({}^{\circ}\)C to 30.1 \({}^{\circ}\)C, and the NSA samples' temperatures ranged from 35.6 \({}^{\circ}\)C to 44.4 \({}^{\circ}\)C (Figure 4a). The total dissolved solids (TDS) measurement is usually used as a general indicator of water quality [44]. Groundwater is classified as a fresh, brackish, and saline [45]. Results (Table 1) show that the Quaternary groundwater's TDS measurements ranged from 426 to 9975 mg/L with a median value of 2472.6 mg/L, identifying it as a fresh to saline water type. The PNA samples' TDS measurements ranged from 1134 to 6969 mg/L with a median of 4348.9 mg/L, identifying it as a fresh to saline water type. The NSA samples' TDS measurements ranged from 1496 to 1737 mg/L with a median value of 1676 mg/L, identifying it as brackish water (Figure 4b). In the upper region of the analyzed area the Quaternary and PNA groundwater had lower TDS values (Figure 1) which may be attributed to the direct recharge from local precipitation. In addition, the Quaternary groundwater downward, close to the River Nile, had lower TDS values, indicating that the River Nile percolates into the aquifer. In general, most of the major ions (Na+, Mg2+, Ca2+, \(\text{SO}_{4}\text{2}^{-}\), and Cl-) were positively correlated with TDS (Figure 5a-f), indicating that their concentrations' increase was controlled by flow path, geochemical processes, and water-rock interaction between the groundwater and aquifer matrix.  
Figure 4: Box plot for the (**a**) temperature (\({}^{\circ}\)C) and (**b**) TDS (mg/L) of groundwater in the Wadi Qena basin.  
Figure 5: _Cont_.  
Figure 5: Major ions concentrations (mg/L) versus total dissolved solids (TDS) in mg/L relationships for groundwater wells tapping aquifers in the Qena basin (**a**) Ca2* Versus TDS, **(b**)** Mg2+ versus TDS, **(c)** Na++K+ versus TDS, **(d)** HCO3– versus TDS, **(e)** Cl– versus TDS, and **(f)** SO42– versus TDS.
## 2 Materials and Methods
### Methodology
#### 2.2.3 Data Selection  
The spatial classification used to evaluate the GK2A fog detection performance over inland and coastal regions was based on the lsmask provided in the GK2A fog product. The temporal classification was determined by SZA at each pixel: SZA \(<\) 80\({}^{\circ}\) was considered daytime, 80\({}^{\circ}\)\(\leq\) SZA \(<\) 88\({}^{\circ}\) twilight, and SZA \(\geq\) 88\({}^{\circ}\) nighttime.  
As shown in Table 4, Flag 0 represents nominal data with complete channel availability and valid detection. Flags 1 to 13 indicate cases of partial input data loss or invalid prior detection data [28]. Flag 15 (mid- to high-level clouds) accounted for 43.34%, while Flag 14 (snow contamination) accounted for 3.73%. Pixels affected by clouds or snow cover were excluded from the evaluation to ensure reliable fog/no fog classification based on the quality flags and product values (see Table 2), as these conditions often prevent accurate satellite observation [25; 29].  
In this study, six sub-algorithms excluding the ocean category were evaluated using available ground-based validation data. Moreover, fog performance was evaluated on a monthly basis to account for the seasonal variability in fog occurrence. A total of 156,369 scenes (99.2%) were used in the analysis out of a theoretical maximum of 157,680 scenes (3 years \(\times\) 365 days/year \(\times\) 24 h/day \(\times\) 6 scenes/h), excluding scenes with missing data due to operational issues.
## 3 Materials and Methods
### Workpiece Material  
For the realization of the milling tests with barrel end-milling cutters, the material chosen for the workpieces was titanium alloy (Ti-6 Al-4V Grade 5, as specified in ISO 5832-3:2016 [35]), due to its mechanical properties and its relevance in industrial applications where barrel end-milling cutters are used.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Company**} & \multirow{2}{*}{**Programming**} & \multicolumn{2}{c}{**Code**} & \multicolumn{2}{c}{**Tool Type**} \\ \cline{3-6}  & & & & **(Radius)** & **(Tooth No.)** & **(Coating)** \\ \hline \multirow{3}{*}{EMUG} & 20 & \multirow{3}{*}{3540L/3541L} &.12250A & 250 & 3 & \\  & 42.5 & &.12200A & 200 & 3 & \\  & — & 3538L &.12080A & 80 & 4 & \\ \hline \multirow{3}{*}{SECO} & 20 & \multirow{3}{*}{JH744120T2R3R250.0Z4 SIRA} & 250 & 4 & \\  & — & & JH734120X2R2R80.0Z4 SIRA & 80 & 4 & \\ \hline \multirow{3}{*}{ISCAR} & 20 & \multirow{3}{*}{ETB-R3R250A12/20-4C12-83} & 250 & 4 & \\  & 15.98–18.38 & & EOB-R3R80A24/8-4C12-83 & 80 & 4 & \\ \hline \multirow{3}{*}{InovaTools} & — & 633 & 040.00 & 90 & 4 & VAROCON \\  & 18 & 634 & 040.00 & 450 & 4 & VAROCON \\ \hline \hline \end{tabular}
\end{table}
Table 1: A selection of barrel end-milling cutters analyzed.  
Figure 1: Positioning of barrel tools in relation to the workpiece.  
For this purpose, the semi-manufactures used were parallelepipeds, a geometry selected to simplify machining operations, positioning during chipping and measurement of the resulting surfaces. More specifically, the machining program for machining with barrel end-milling cutters was developed using a semi-fabricated assembly consisting of a clamping pan and a titanium parallelepiped.  
To ensure the accuracy and reproducibility of the results obtained from the processing of each specimen, strict adherence to the dimensions of the specimens was required. Accordingly, the titanium specimens were machined to a nominal length \(\times\) width \(\times\) height of 59.5 \(\times\) 48 \(\times\) 50 mm, with a dimensional tolerance of +0.05 mm after each dimension.  
The Al7175 used to make the device is shown in Figure 2.  
Table 2 shows the chemical composition and mechanical characteristics of alloy 7175 according to the certificate.
# Video Temporal Grounding with Multi-Model Collaborative Learning
## 4 Experiments
### Ablation Studies
#### 4.7.4 Effectiveness Analysis of the CLIP-Guided Module  
In the CLIP-guided module, both the number of sampled video frames \(n_{f}\) and the similarity threshold \(\tau\) play a key role in determining the quality of pseudo-labels, thereby shaping the outcomes of inter-model knowledge transfer as well as final performance. In this subsection, we separately discuss the impact of varying the number of video frames and the similarity threshold on the MMCL framework, with the corresponding results presented in Figure 7. First, holding the similarity threshold constant at \(\tau=0.4\), we gradually raise the number of sampled frames. As depicted in Figure 7a, the model's performance (mIoU) progressively increases alongside the number of frames. This indicates that a higher frame count enriches the temporal scope and contextual fidelity of the pseudo-labels, effectively expanding the reservoir of knowledge they convey. Nevertheless, upon reaching 64 frames, performance gains level off or marginally drop because incorporating excessive frames does not translate into significant feature benefits but rather introduces unwarranted noise and squanders computational overhead. Subsequently, keeping \(n_{f}=32\) constant, we adjust the similarity threshold \(\tau\) to gauge how performance responds. As illustrated in  
Figure 6: Effect of the consistency threshold (\(\lambda\)) and the dynamic adjustment factor (\(\gamma\)) on model performance.  
Figure 7b, the model's performance follows a nonlinear trajectory in response to variations in the similarity threshold \(\tau\). A too-low threshold incorporates excessive low-grade segments in the pseudo-labels, weakening their utility in guiding optimization. Conversely, a too-stringent threshold narrows the scope of pseudo-labels, hindering the capture of the video's broader context and thereby stifling collaborative improvement. In comparison, a moderate threshold (\(\tau=0.4\)) attains an equilibrium between filtering out noise and retaining adequate coverage, yielding pseudo-labels of superior quality for facilitating knowledge transfer. In sum, judiciously determining the number of frames and the similarity threshold is vital for producing robust pseudo-labels, thereby proving indispensable for successful inter-model knowledge transfer and performance enhancement.
# Voltage Ride through Control Strategy of Modular Multilevel Converter under Unbalanced Voltage Sag
## 1 Introduction
The ability of the entire control system to enhance the unbalanced fault ride-through capability of the distributed power generation system was also evaluated by time domain simulations. Furthermore, in Reference [13], a shunt active power filter based on a three-level inverter was employed to reduce both the whole switching power losses and total harmonic distortion (THD). The main contribution of this study is its survey of the prospects of the multilevel inverter being involved as a shunt active filter on the control of the reactive power, as well the harmonics mitigation drawn from a nonlinear load and unbalanced sources. Therefore, an intelligent controller is recommended for a three-level shunt active filter to overcome the asymmetrical conditions on the grid voltages and control of DC link voltage. In general, the objectives and novelties of the current study are described as follows:  
* The development of a dynamic model of the grid-controlled (GC)-MMC, based on a symmetrical component of voltages and currents considering positive and negative sequences;
* The design a fuzzy-sliding model of control to regulate the symmetrical components of upper and lower arm currents and stabilize the SM's capacitor voltages;
* The improvement of the robustness and stability of the controllers; and
* Dynamic performance validation of a proposed controller for the GC-MMC under different conditions, including grid faults and normal situations, through simulation and experimental implementation. This paper is classified as follows: Section 2 presents the modeling of the GC-MMC. Then the proposed control scheme is presented in Section 3. Finally, in Section 4, the simulation results are presented with additional details.
## 3 Measurement Results
### Radar Sensitivity  
To test the Doppler sensitivity of the reconfigurable radar, a corner reflector was positioned in front of the system, as shown in Figure 9a. The motion amplitude, motion frequency, and distance to the radar were isolated and individually swept. The initial test setup used was 1 mm motion at 2 Hz and 1 m away, and its \(I/Q\) response is shown in Figure 9b. From here, the variables of interest were swept until the spectral response did not contain the motion frequency, and the limits of the system are given in Table 3.
# Matrix Adaptation Evolution Strategy with Multi-Objective Optimization for Multimodal Optimization
###### Abstract  
The standard covariance matrix adaptation evolution strategy (CMA-ES) is highly effective at locating a single global optimum. However, it shows unsatisfactory performance for solving multimodal optimization problems (MMOPs). In this paper, an improved algorithm based on the MA-ES, which is called the matrix adaptation evolution strategy with multi-objective optimization algorithm, is proposed to solve multimodal optimization problems (MA-ESN-MO). Taking advantage of the multi-objective optimization in maintaining population diversity, MA-ESN-MO transforms an MMOP into a bi-objective optimization problem. The archive is employed to save better solutions for improving the convergence of the algorithm. Moreover, the peaks found by the algorithm can be maintained until the end of the run. Multiple subpopulations are used to explore and exploit in parallel to find multiple optimal solutions for the given problem. Experimental results on CEC2013 test problems show that the covariance matrix adaptation with Niching and the multi-objective optimization algorithm (CMA-NMO), CMA Niching with the Mahalanobis Metric and the multi-objective optimization algorithm (CMA-NMM-MO), and matrix adaptation evolution strategy Niching with the multi-objective optimization algorithm (MA-ESN-MO) have overall better performance compared with the covariance matrix adaptation evolution strategy (CMA-ES), matrix adaptation evolution strategy (MA-ES), CMA Niching (CMA-N), CMA-ES Niching with Mahalanobis Metric (CMA-NMM), and MA-ES-Niching (MA-ESN).  
Keywords:multimodal optimization problems; multi-objective optimization; matrix adaptation evolution strategy; non-dominated sorting +
Footnote †: journal:
# Multi-Source Data Fusion-Based Grid-Level Load Forecasting
## 4 Discussion
### Comparison with Existing Fusion Approaches  
A comparative analysis of our weighted fusion methodology with existing multi-source data fusion approaches reveals several distinctive contributions. While [PERSON] et al. [9] propose an edge intelligence-based framework for power distribution IoT that addressesdata storage and computing performance through Box-Cox transform Z-score normalization and DS inference-based fusion, their approach primarily targets sensor-level data integration rather than forecast combination. Our methodology fundamentally differs by introducing a comprehensive evaluation framework specifically designed to assess forecast reliability in grid-level applications, where the integration unit is the forecasting result itself rather than raw measurement data.  
Similarly, [PERSON] et al. [36] focus on interoperability challenges of heterogeneous data from micro-synchronosp measurement units, developing a unified information model and distributed processing technology for streaming data. In contrast, our approach advances beyond data standardization to address the quality assessment and optimal weighting of forecasts. The principal component analysis mechanism we employed for weight derivation represents a significant methodological advancement over both approaches, as it systematically captures the multidimensional reliability characteristics of regional forecasts and translates them into quantifiable contribution weights.  
Furthermore, our incorporation of time-varying weights addresses a fundamental limitation in existing fusion approaches, which typically apply static weighting schemes regardless of temporal variations in forecast performance. This dynamic adaptability is particularly critical for grid-level load forecasting, where forecast reliability exhibits significant diurnal patterns. The empirical validation across six diverse regions demonstrating substantial performance improvements (24.67% for MAPE) provides compelling evidence for the effectiveness of our approach in addressing the specific challenges of regional grid-level load forecast integration.
###### Abstract  
(1) Background: Attention-Deficit/Hyperactivity Disorder (ADHD) is typically first diagnosed in early childhood. Medication and cognitive behavioural therapy are considered effective in treating children with ADHD, whereas these treatments appear to have some side effects and restrictions. Virtual reality (VR), therefore, has been applied to exposure therapy for mental disorders. Previous studies have adopted VR in the cognitive behavioural treatment for children with ADHD; however, no research has used VR to develop social skills training for children with ADHD. This study aimed to develop a VR-based intervention (Social VR) to improve social skills in children with symptoms of ADHD. Prior to conducting the pilot trial to assess the effectiveness of Social VR, valuable user feedback was gathered regarding the mechanics of Social VR, satisfaction and motion sickness. This study presented the development and preliminary usability of Social VR to enhance social interaction skills among children with ADHD. (2) Methods: The development process of the Social VR intervention was demonstrated. The Social VR intervention consisted of three scenarios, namely MTR, Campus and Market and Restaurant. In the usability study, 25 children with ADHD were recruited to test the Social VR during the preliminary usability stage of a clinical trial at preinclusion. The participants completed a survey about their experience of playing Social VR, satisfaction, and motion sickness. (3) Results: The participants indicated the three conditions had easy-to-follow instructions, were easy to pick up, and that they understood when the situations changed. The control and beauty of the graphics of Market and Restaurant were relatively lower compared with those of MTR and Campus. The three scenarios are applicable to children diagnosed with any subtype of ADHD. (4) Conclusion: The participants were satisfied with Social VR. Social VR was generally considered realistic and immersive. Further trials to assess the feasibility and efficacy were discussed. If proven effective, VR-based intervention can be an adjunctive approach to current multimodal training for children with ADHD.  
attention-deficit/hyperactivity disorder; virtual reality; social skills; cognitive behavioural therapy; usability; motion sickness 2023
# A Survey on Botnets: Incentives, Evolution, Detection and Current Trends
## 7 Current Trends and Challenges
### Cloud-Based Botnets  
Finally, the normalisation of cloud-computing has allowed for greater computing power to both aid and combat botnets. This increase in computing resources and publicly available communication services, such as Google Cloud, has also been exploited by hackers to create botnets in the cloud. As cloud deployments are virtually instantaneous and on-demand, the cloud allows bot masters to dynamically scale the size of their botnets to match the needed computing power for attacks. Additionally, cloud services have been shown to be used for C&C communications between bots and bot masters, masquerading as benign user traffic [187]. Mitigation techniques based on IPs and locations are shown to be ineffective due to the relative in-deterministic nature of cloud deployment locality. The cloud can also be seen as a potentially attractive option for botnet research due to its low price, allowing researchers to instantly create botnets without having to make ethically questionable decisions such as infecting user computers in the wild [87; 233].
# Evaluation of Methods Based on CPTu Testing for Prediction of the Bearing Capacity of CFA Piles
## 2 Materials and Methods  
To evaluate the bearing capacity of CFA piles calculated by the above-mentioned methods, a static load test was conducted on selected piles in pile groups of bridge foundations during construction. Cone penetration tests were then proposed to link the outputs of CPT testing and experimental measurements on piles which can be considered as a reference database. Detailed description of investigated geological conditions at the site, tested CFA piles, and CPT testing is mentioned in the following sections.
# A Framework for Fall Detection Based on OpenPose Skeleton and LSTM/GRU Models
## 5 Conclusions  
This paper proposes a fall detection framework using OpenPose to extract human skeleton from captured frames and recurrent neural network, long short-term memory and gated recurrent unit to detect fall based on skeleton data. Due to the correlation of the human skeleton, we believe that the change trajectory of the joint points is related to the human movement. This method has been shown to work well in a complex space environment with lower equipment costs. However, the joint points will be lost in some postures and actions, causing the model to have coagulation during training. Therefore, we will move the joint points to the set relative position and interpolate part of the data to improve the excessive noise and unnormalized happening. Recursive neural networks can effectively help learn the time changes in human joint points and reduce training time. Therefore, this paper proposes a fall detection model that learns the changes in human joint points in continuous time. The experimental results show that the fall detection accuracy of the proposed model is 98.2%, which outperforms the baseline 88.9%.  
Conceptualization, C.-B.L. and Y.-F.H.; methodology, C.-B.L. and Y.-F.H.; software, W.-K.K.; validation, C.-B.L., W.-K.K. and Y.-F.H.; formal analysis, C.-B.L. and Y.-F.H.; investigation, C.-B.L. and Y.-F.H.; resources, C.-B.L. and Y.-F.H.; data curation, C.-B.L. and W.-K.K.; writing--original draft preparation, W.-K.K. and Y.-F.H.; writing--review and editing, C.-B.L., and Z.D.; visualization, Z.D.; supervision, C.-B.L.; project administration, C.-B.L.; funding acquisition, C.-B.L. All authors have read and agreed to the published version of the manuscript.  
Figure 18: Linear interpolation to compensate for missing points. (**a**) Point 15 (turning point) is missing; (**b**) Points 11–19 (including turning points) are missing.  
Funding: This research was funded by the Ministry of Science and Technology in Taiwan under Grant No.: MOST 108-2637-E-324-004.