esa-sceva/satcom-chunk-collection huggingface dataset:
# Practical Performance Analyses of 5G Sharing Voice Solution
## 4 Voice Services Based on 5G Sharing
### SA Sharing EPS Fallback Process
#### 4.2.1 EPS Fallback Based on Handover  
As can be seen in Figure 6A, the UE sends a SIP INVITE message to the 5 GC requesting the voice session setup after the 5G entry registration process. After the gNodeB receives the PDU SESSION RESOURCE MODIFY REQUEST message, it directs the gNodeB to establish a voice-dedicated bearer for 5 QI1. Afterward, the gNodeB sends the inter-system B1 event measurement and receives the measurement report. gNodeB replies to the 5 GC rejecting the setup of PDU Session 5 QI1 and directs ims-voice-eps-fallback-or-fallback-triggered. gNodeB determines based on the handover parameter configuration and UE capability. The EPC establishes a handover request to the eNodeB and, after receiving the response, sends a successful handover request response message from the eNodeB to the 5 GC. 5 GC establishes a handover command to the gNodeB. gNodeB sends a handover command to the UE. Finally, the handover-based EPS fallback is completed. The terminal access unit (TAU) process and the process of setup VoLTE will be specifically analyzed in the subsequent sections on the call setup delay.  
The communication cost of handover-based EPS fallback is shown in Equation (4).  
\[T_{EPSB-\mathrm{HO}}=T_{TAU}+T_{\mathrm{VoLTE}}+15\delta+\varepsilon+\eta+7 \gamma+2(\theta+\mu) \tag{4}\]  
As can be seen in Figure 6A, there are fifteen times of communication between UE and gNodeB, seven times of communication between gNodeB and 5 GC; two times of communication between 5 GC and EPC, and between EPC and eNodeB, the communication between the remaining entities is only one time.
# Characterization and Finite Element Modeling of Microperforated Titanium Grade 2
## 3 Results and Discussion
### Nakajima Test Results  
Microperforated specimens oriented in longitudinal and transversal orientations have similar cracks, but specimens oriented in the diagonal orientation crack look different. Exactly as happened in tensile testing, cracks always move along the shortest path between two holes that correspond to longitudinal and transversal orientations.  
The FLC points for microperforated samples are presented in Table 4, which were calculated as the mean of three repetitions for each geometry. Variability between repetitions is less than 3% in all cases. Figure 11 shows the FLCs for microperforated samples and compares them with ordinary titanium grade 2 obtained from the literature ([PERSON] and [PERSON], 2017). The microperforation significantly reduces the formability of titanium grade 2 sheets. The mayor strain in unperforated material at the plane strain condition is approximately 32%, and it reduces to 10-13% when the material is perforated. On the other hand, orientation does not play a significant role, only the formability of transversal specimens is slightly worse than other specimens. It seems like it is related to the fact that a crack always moves on the shortest way between two holes.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \multicolumn{2}{c}{**Longitudinal**} & \multicolumn{2}{c}{**Transversal**} & \multicolumn{2}{c}{**Diagonal**} \\ \cline{2-7}
**Geometry** & **Minor** & **Major** & **Minor** & **Major** & **Minor** & **Major** \\  & **Strain** & **Strain** & **Strain** & **Strain** & **Strain** & **Strain** \\ \hline G1 & \(-0.164\) & \(0.287\) & \(-0.168\) & \(0.263\) & \(-0.230\) & \(0.348\) \\ G2 & \(-0.127\) & \(0.254\) & \(-0  
Another important piece of data obtained from the Nakajima test is the punch load-stroke curves (Figure 12). The punch-stroke curves for different orientations vary significantly, mainly at the end of the tests. At the beginning, the three orientations are remarkably similar for all geometries; however, after a certain stroke (near 15 mm), the longitudinal direction is appreciably stronger and requires more stroke to break. Diagonal and transversal orientations overlapped but transversal (green) always broke before diagonal (red). All these conclusions prove that anisotropy plays an important role in the microperforated material studied in this paper.
# Adaptive Model-Free Coupling Controller Design for Multi-Axis Motion Systems
## 3 Adaptive Model-Free Coupling Controller Design Using RFNN
### Comparison Controller Using FNN, RFNN  
Here, we compare adaptive model-free coupling control while using RFNN and FNN, where the FNN is a special case of RFNN without feedback layer. From Equation (4), dynamic model becomes complex time-vary system through transformation matrix \(F(t)\), in order to illustrate the advantage of using RFNN, a comparison results of adaptive model-free contour controller using RFNN and FNN are introduced. As far as we know, RFNN is dynamic network and is more suitable for handling time-varying problem than FNN. The desired trajectory and the initial condition are the same as above description. Figure 8 shows the simulation results (blue-line: desired trajectory; green-line: adaptive model-free coupling control using FNN). Figure 8a shows the system trajectories, Figure 8b is the corresponding contour error, and the corresponding trajectories and control efforts of each axis are shown in Figure 8c,d, respectively. Besides, Table 2 shows the performance of different case in maximum contour error, total contour error, and RMSE. Similar to the above description, from Figure 8 and Table 2, we can observe that controller using RFNN has better performance than the controller using FNN. We conclude that that RFNN is more suitable for handling time-varying problem than FNN.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Case 1** & **Case 2** & **Case 3** \\ \hline Max. contour error (mm) & 0.0118 & 15.0848 & 13.8432 \\ \hline Total contour error (mm) & 26.3217 & 106000 & 60349.14 \\ \hline RMSE (mm) & 0.1660 & 9.0539 & 4.8477 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Comparison results of adaptive model-free controller.  
Figure 7: Simulation results, (**a**) performance of different case in X-Y-Z plane, (**b**) contour error of different cases, (**c**) performance of each axis, and (**d**) control effort.
## 4 Practical Experiments
### Boverbream
#### 4.2.3 Change Detection in South Smerstabb Massif  
A comparative analysis of the southern Smerstabb Massif, including Boverbren, was conducted to assess glacier changes by comparing a 2021 PlanetScope DEM with one acquired by the Norwegian authorities in September 2013 from aerial images using aerotri-angulation. The latter DEM has a GSD of 1 m and an average vertical accuracy of 0.6 m, with maximum reported errors of 2 m in steep terrain. Although the dataset does not cover the entire extent of the area represented in the PlanetScope DEM, it nonetheless provides valuable insights into elevation changes in the southern Smerstabb Massif. The temporal gap of eight years is particularly relevant as long-term monitoring by the Norwegian Water Resources and Energy Directorate (NVE) has documented significant glacier retreat during this period [34], and thus a substantial loss of ice volume within the glacier's delineated area is expected when comparing the DEMs.  
The results of the DoD analysis are presented in Figure 16. As anticipated, the analysis reveals substantial negative elevation changes across the entire Smerstabb Massif. High positive deviations are observed in areas influenced by glacial lakes or shadowed regions as PlanetScope scenes are acquired sun-synchronously during the local morning.  
Focusing on Boverbren, the distinct tapering shape of the glacier terminus is clearly visible and aligns well with glacier outlines from the 2000s. Although detailed information on ice thickness changes at the terminus is unavailable, the observed shifts in the glacier front position closely match the outlines documented in the RGI dataset, further supporting the validity of the detected changes. The differences in the southern part of the Smerstabb  
Figure 16: Change detection in the southern Smerstabb Massif. **Left**: DoD derived from the 2021 PlanetScope DEM and the 2013 DEM from aerial images. **Right**: histogram of elevation changes (in meters) within the ROI defined by the glacier outlines.  
Massif show a mean and median decrease of approximately \(-15\) m. This is plausible when considering observations reported by sources such as [34].
# Indoor Localization Using 6G Time-Domain Feature and Deep Learning
## 5 Conclusions  
A ResNet neural network architecture with channel and spatial attention is proposed for indoor positioning by using time-domain data. ResNet's deeper architecture with residual connections provides a powerful alternative for handling noisy data. Simulation results demonstrate that incorporating CLAB yields an improvement in RMSE, making it an effective approach for enhancing 6G indoor positioning accuracy. The channel attention SLAB mechanism also contributes to performance improvement. These findings highlight the potential of attention-enhanced ResNet models for improving localization precision in noisy environments. By incorporating either CLAB or SLAB into the ResNet architect  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Performance Models** & **ResNet** & **ResNet with CLAB** & **ResNet with SLAB** & **ResNet with CLAB and SLAB** \\ \hline Computation Time & 150 min & 155 min & 160 min & 165 min \\ \hline \hline \end{tabular}
\end{table}
Table 3: Computation Time for training each model.  
Figure 9: The loss function versus epoch with interference.  
ture, the positioning error can be reduced to as low as approximately 7 cm. Moreover, the results of this study will offer insights into the relative strengths of these models in noise resilience and positioning accuracy, which are crucial for the success of real-world positioning systems.  
While our method demonstrates strong performance in simulated indoor environments using ray-traced CIR data, certain limitations remain. Real-world deployment may introduce practical challenges such as hardware variability across different devices and environmental dynamics due to moving objects or changes in room layout. These factors could affect the model's generalization ability. Addressing these challenges will require further validation of real-world data and potentially the application of domain adaptation techniques such as transfer learning. Future research could explore global channel and spatial attention mechanisms to further optimize the localization performance.  
Conceptualization, E.H.L.; Data curation, C.-E.C.; Formal analysis, E.H.L.; Funding acquisition, E.H.L.; Investigation, E.H.L.; Methodology, P.-H.C.; Project administration, C.-C.C.; Resources, H.-Y.W.; Software, H.-Y.W.; Supervision, C.-C.C.; Validation, P.-H.C.; Visualization, C.-E.C.; Writing--original draft, H.-Y.W.; Writing--review & editing, P.-H.C. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Data Availability Statement: Data are contained within the article.  
The authors declare no conflict of interest.
## 3 System Description
### System Model
#### 3.2.1 Room and Reflector Models  
Figure 4a illustrates the OBAN system model that was considered in this study. The tier-II DL connection comprises of five VLC transmitters (TP\({}_{1}\), TP\({}_{2}\),...TP\({}_{5}\)) distributed on the ceiling, where TP\({}_{n}\) (x,y,z) denotes the transmitter position with coordinates \((x,y,z)\) in meters and '\(n\)' represents the transmitter number. Based on [13], an LED array of \(50\times 50\) is used for each luminaire. The DL receiver is assumed to be a 1 cm\({}^{2}\) silicon-based positive-intrinsic-negative (PIN) PD placed on the patient's arm. Conversely, for the UL connection, an on-body IR transmitter is placed together with the DL VLC detector, whereas the IR receivers are assumed to be placed on the ceiling alongside the DL transmitters represented by (RP\({}_{1}\), RP\({}_{2}\),...RP\({}_{5}\)). To establish an OBAN link between the Txs and Rx, the most performing link configuration is the LoS; nevertheless, a perfect LoS connection may not always be feasible due to random human body movements. Alternately, since, non-directed LoS links can support mobility scenarios in indoor environments; therefore, this study employs LoS with non-directed first-order reflections (see Figure 4b). Accordingly, it is assumed that the patient could be present at any random location along the XY-plane in the indoor space (see Figure 4). Besides, even though the receiver height may vary with the posture under consideration, it is assumed to be at the desktop level of 0.85 m, unless stated otherwise.  
To perform the ray-tracing simulations, a room that has often been used in the literature with the dimensions of \(5\times 5\times 3\) m\({}^{3}\) has been considered [9; 11]. Given the typical low data-rates that are used in OBANs, the room furniture has a negligible impact on the main characteristics of the channel [28; 29]; hence, it is not considered in the study. However, all of the lateral room surfaces are modeled as the first order Lambertian reflectors, which bear a constant reflection coefficient. Besides, to study the effects of LED lamp arrangements, two placement techniques have been considered, namely, CLQ envisaged for attocells in [13] (Figure 4a) and the proposed-ColQ (Figure 4b). CLQ employs four transmitters that are placed at the center of each quadrant in the room with an additional LED lamp located  
Figure 4: LED lamp placements for (**a**) centrally lit quadrants (CLQ) and (**b**) corner illuminated quadrants (ColQ).  
at the geometrical center of the room itself. Conversely, CoIQ considers placing the LED lamps around each corner of the room with one transmitter that is located in the center.
# LaRoAwan and Urban Waste Management--A Trial
## 3 Related Work  
The applicability of LoRa to smart cities has long been studied and researched. In [5] the authors evaluate the applicability of LoRa to smart cities by tracking the number of published works and the same smart city vertical this paper addresses. From here they determined that the waste management is the second most addressed vertical on a smart city by current research, with environment leading the table.  
LoRa is not the only technology used for waste management in cities. In [6; 7; 8; 9; 10; 11; 12; 13], multiple Low Power Wide Area Network types are used to address the waste management problem, specifying complete solutions from the sensor to the application, addressing intelligent routing of waste trucks [14; 15; 16] and energy [17; 18; 19; 20; 21; 22; 23; 24; 25; 26; 27; 28; 29; 30; 31; 32; 33; 34; 35; 36; 37; 38; 39; 40; 41; 42; 43; 44; 45; 46; 47; 48; 49; 50] as two of the main issues with this kind of application.  
However, regarding the practical application of LoRa based commercial sensors to commercial waste containers, in place and being used daily, the related research is scarce,  
Figure 1: LoRaWAN architecture.  
Figure 2: LoRaWAN layers.  
being [14; 51; 52] some of the most relevant works addressing the research on the sensor type up to the application and business case, all of them with trials in European cities. In [14], the city of Salamanca, Spain was used as a use case, the authors used sensors developed by themselves together with commercial waste containers (although only surface ones). In [51] the authors also developed the sensors and mostly addressed the business case, using The Things Network as the underlying network for their trials, deployed in Herring, Denmark, the same network as the one used on our own trials. In [52], the authors depict a case study in Luxembourg for improving the waste collection process. The presented case study uses Sigfox as an underlying LPWAN for the filling level sensors placed at the waste containers. In this study, the authors included commercial sensors and waste containers, placing them at indoor scenarios, unfortunately the main objective of this study was the optimization of the waste collection process and not the evaluation of the impact of the different scenarios on the connectivity.  
These works mostly use LoRaWAN as a possible network layer and lack trials on the network planning and connectivity requirements when using commercial solutions. This leads us into this work, effectively validating the research on sensors, networks, energy efficiency, and communication technologies when applied to real use cases considering the currently used waste containers in a large city, its landscape, and a network using commercially available equipment.  
Another conclusion on the related work is that Europe is leading the research, using LPWAN technologies, to address the smart city vertical of urban waste management, with LoRaWAN being the most prominent underlying network layer.
## 3 Experiments, Results and Discussion  
The experiments were carried out on-site at the Faculty of Civil and Geodetic Engineering in Ljubljana, Slovenia. The tests were performed under different conditions and at different times in static and kinematic modes. Reference points and kinematic survey outlines are shown in Figure 2 (A). The reference point positions were determined by precise GNSS and total station measurements. An extending roof turret above the rooftop of the building (partially visible in Figure 2 (A) and represented by the dark shape in Figure 2 (B)) was used to simulate adverse conditions, where the signals become attenuated and reflected.  
Figure 2: **(A)** Reference points: (a) normal conditions; (b) adverse conditions; (c) indoors. **(B)** Kinematic survey outlines on an orthophoto image: (d) mixed conditions; (e) mixed conditions; (f) adverse conditions.  
The horizontal coordinates of the surveyed points are expressed as \(N\) and \(E\) in a projection plane, while the vertical component is expressed as the height above ellipsoid \(h\). The observables used in the positioning procedure are labelled as in RINEX files: \(C1\) code pseudoranges and \(D1\) Doppler values. All tests were carried out and processed in a 1 Hz kinematic mode.  
Several autonomous solutions were determined from each survey: C1 (code-based positioning); D1 (Doppler positioning); C1&D1 (common processing of code and Doppler observations); custom C1&D1 (as described in Section 2.1.); NMEA (positions, determined by the receiver, extracted from NMEA messages). The elevation angle weighting and SNR weighting were also tested. DGPS solutions are labelled DGPS, whereas the conditional DGPS is represented by the label cDGPS. The symbols I and T represent the use of ionosphere and troposphere models respectively.
# HCLE: Hybrid Clustering Approach for Extending WBAN Lifetime
## 4 Materials and Methods
### HCEL Routing Protocol
#### 4.2.2 Parent Node Selection
The pseudo-code of the parent node selection process is depicted in Algorithm 1, while the flowchart for this process is shown in Figure 2.  
```
1:\(N\) (Number of nodes), \(d[1..N]\) (distances from sensor nodes to the sink), \(RE[1...N]\) (residual energy levels of sensor nodes), \(RSSI[1..N]\) (RSSI values of sensor nodes), \(\tau\) (number of serving nodes for parent node), \(Th\) (energy threshold), one-hop nodes' id
2:\(PN\) (Parent nodes' id)
3:for\(i=1\) to \(N\)do
4:if\(i\) not in one-hop nodes' id then
5:\(CF[i]=\frac{d[i]\times RSSI[i]}{RE[i]}\)\(\triangleright\) Cost Function
6:endif
7:endfor
8:\(serve_{count}[1..N]=0\)
9:\(SortedCF=Sort(CF)\)\(\triangleright\) Ascending Sorting
10:\(indices[1..N]=0\)
11:for\(i=1\) to \(N\)do\(\triangleright\) Store indices of nodes after sorting cost function
12:\(indices[i]=IndexOf(CF,SortedCF[i])\)\(\triangleright\) Get indices of nodes after sorting
13:endfor
14:for\(j=1\) to \(N\)do\(\triangleright\) Static Clustering
15:for\(i\) in indicesdo
16:if\(serve_{count}[i]<\tau\) and \(RE[i]>0\) and \(RE[i]>Th\)then
17:if\(i\)\(!=j\)then
18:\(serve_{count}[i]+=1\)
19:endif
20:endif
21:endfor
22:\(PN[j]=index\)
23:endfor
24:if\(RE[1..N]<=Th\)then\(\triangleright\) Dynamic Clustering
25:for\(j=1\) to \(N\)do
26:for\(i\) in indicesdo
27:if\(serve_{count}[i]<\tau\) and \(RE[i]>0\) and \(RE[i]<=Th\)then
28:if\(i\)\(!=j\)then
29:\(serve_{count}[i]+=1\)
30:endif
31:\(index=i\)
32:endif
33:endfor
34:\(PN[j]=index\)
35:endfor
36:endif
```  
**Algorithm 1** Parent Node Selection Process
# Facile Fabrication of a Low-Cost
## 1 Introduction  
Lead is widely used as a raw material in industrial production. Lead ions (Pb\({}^{2+}\)) are often found in lead storage batteries, lead ore smelting, and recycled lead industrial wastewater [1]. Pb\({}^{2+}\) in wastewater can be absorbed and enriched by aquatic animals and plants and then enter the human body through the food chain, thereby posing serious damage to the nerves, digestive systems, kidneys, and endocrine systems of humans [2; 3]. Children are more sensitive to Pb\({}^{2+}\) than adults, and excessive Pb\({}^{2+}\) can cause mental decline and behavioral abnormalities among children [4; 5]. Therefore, new methods and materials for effectively and selectively removing Pb\({}^{2+}\) from wastewater must be developed.  
Previously, many synthesized materials, such as one-dimensional (1D) nanofibers [6; 7], two-dimensional (2D) films or membranes [3; 8; 9], and three-dimensional (3D) scaffolds [10; 11; 12], have been utilized as effective absorbents for treating Pb\({}^{2+}\)-containing water systems. 1D and 2D nano-adsorbents have a high adsorption capacity and adsorption rate for Pb\({}^{2+}\) due to their high specific surface area and chemical activity, but the preparation of these nanomaterials usually requires stringent conditions, such as a high temperature, high pressure, high purity reagents, etc. In addition, these nano-adsorbent materials are difficult to recollect because of their small size. Macroscopic 3D porous material can overcome the above shortcomings. It not only provides a high surface area, but also facilitates solid-liquid separation. To achieve an economical use of the synthesized absorbents, animportant aspect is to find low-cost and source-rich natural materials for fabricating various functional nanomaterials [13; 14].  
Sodium alginate is a natural polysaccharide with an excellent biocompatibility and biodegradability. This molecule contains a large amount of carboxyl and hydroxyl functional groups that can complex metal ions [15]. Therefore, sodium alginate can also be used as a medical antidote for treating heavy metal ion poisoning [16]. However, alginate aerogels have poor mechanical properties. After repeated use, the aerogel structure can be easily destroyed, thereby resulting in an unstable adsorption capacity for heavy metal ions [17]. This kind of material shows improved mechanical properties given its special adhesion. In addition, the polyacrylamide molecule contains a large amount of amino groups that can chelate with metal ions, thereby adsorbing heavy metal ions in water [18; 19].  
In this work, to improve the mechanical properties of alginate-based aerogel, we modified polyacrylamide on alginate salt by applying a simple chemical grafting technique and then prepared a novel sodium alginate/polyacrylamideamide (Alg-PAM) composite aerogel by applying the vacuum freeze-drying technique. We then used this aerogel to remove Pb\({}^{2+}\) from wastewater, characterized its morphology and chemical composition, and studied its adsorption effect on Pb\({}^{2+}\) under different experimental conditions.