esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Selected Topology and Slot/Pole Combinations  
In order to compare the effect of eccentricity on different slot/pole combinations of both modular and non-modular PMSMs, tooth coil windings (TCW) were adopted since they allow a higher power/weight ratio due to the shorter end winding turns, lower cogging torque, and compactness when compared with the distributed windings [32]. The modular machine is considered to have U-Shaped stator segments and surface-mounted magnets as depicted in Figure 1b as they have been of interest in the last years for fault-tolerance applications [15,21]. The main data of the machines and their design parameters are presented in Table 1 and schematized in Figure 2. The machines assessed in this work aim to provide maximum mean torque within dimensional constraints, following the optimization criteria established in [17,21]. These machines represent low-power scaled prototypes with a rated power of 5 [kW], considering a current density of 10 A/mm\({}^{2}\) and a speed range of 0 to 6000 [RPM].  
In turn, the slot/pole combinations were selected with the aim of covering different values of slots per phase per pole (\(q\)) given by:  
\[q=\frac{Q_{s}}{2 pm}, \tag{1}\]  
where \(Q_{s}\) is the slot number, \(2p\) is the pole number, and \(m\) is the number of phases. For the case of TCW-PMSM, it is recommended to adopt a value of \(q\) between 0.25 and 0.5 [32],which is the reason why the selected slot/pole combinations are within this range. The combinations evaluated in this work are summarized in Table 2, which also shows their winding layouts. For all considered designs, the coil pitch is equal to 1 slot, as documented in [32].  
In addition, machines with dissimilar differences between the slot number (\(Q_{\text{s}}\)) and the pole number (\(2p\)) are considered in this work from 2 to 6, as addressed in [33].
# Convergence Check Phase-Field Scheme for Modelling of Brittle and Ductile Fractures
## 1 Introduction
Although the three-layer staggered algorithm [27], which is also part of the former research of the authors of this paper, is advantageous by its robustness, this paper proposes a new approach where the third mesh layer is replaced by a single, special-purpose finite element controlling convergence and exchange of the solution variables among the displacement and phase-field mesh layer. The proposed algorithm is implemented into FE software ABAQUS [56] via user subroutines, and it is applicable to general damage phenomena, encompassing brittle and ductile fractures in monotonic and cyclic loading regimes. The proposed methodology assumes a small-strain setting. However, as will be demonstrated, the newly proposed algorithm is easily extended towards large-strain theory. For the problems of the high-cyclic fatigue phenomena, the cyclic skipping technique is utilised. This paper is organised as follows. Section 2 presents the basic relations of the theoretical background and numerical implementation of the phase-field method. Section 3 deals with numerical implementation in the finite element method. Section 4 describes a novel staggered phase-field algorithm, namely, the convergence check phase-field (CCPF) algorithm, along with cycle-skipping methodology. Section 5 demonstrates the efficiency of the CCPF scheme regarding the usual benchmark problems of brittle, ductile, and fatigue damage for small- and large-strain assumptions. The results obtained by the CCPF scheme are then compared to the results of the RCTRL algorithm, with comparison of CPU time. In the end, Section 6 provides some concluding remarks on the newly proposed scheme.
# 3 GPP Evolution from 5G to 6G: A 10-Year Retrospective
## 4 3 GPP Release 17: Expansion of 5G Horizons
### New Features  
Release 17 introduced NTN by integrating satellites and high-altitude platforms into 5G [63; 64]. Figure 4 provides an illustration of 5G NTN architecture. Key enhancements in Release 17 addressed challenges such as long latency, Doppler shifts, and large cell sizes. NTN supported mobility across terrestrial and non-terrestrial systems, with enhanced synchronization, handover, and signaling mechanisms. Flexible service link configurations enabled Earth-fixed, quasi-Earth-fixed, and Earth-moving cell coverage. Enhanced radio frequency (RF) and RRM ensured seamless connectivity for NTN-capable devices. With support for geosynchronous (GSO) and non-geosynchronous (NGSO) satellites, NTN can bridge gaps where terrestrial networks (TNs) are impractical or unavailable.  
NR multicast and broadcast services (MBS), introduced in Release 17, offered efficient point-to-multipoint data delivery modes, addressing use cases like public safety, V2X, live video, and IoT applications [65]. The MBS multicast mode supported high-QoS services for UEs in RRC_CONNECTED, utilizing group scheduling and HARQ feedback. Dynamic point-to-point and point-to-multipoint switching optimized scheduling based on QoS and link conditions. Lossless handovers ensured data continuity for multicast sessions. The MBS broadcast mode catered to lower-QoS services, offering downlink-only delivery for UEs in all RRC states [66]. Features like MBS frequency prioritization and interest indications supported service continuity, enhancing system efficiency and user experience.  
RedCap device support was introduced in Release 17, enabling low-complexity and power-efficient operations for IoT applications such as industrial sensors, wearables, and surveillance [67]. RedCap UEs supported reduced bandwidths (20 MHz in FR1, 100 MHz in FR2), limited antenna configurations, and fewer downlink MIMO layers. They excluded features like CA and DC. Enhanced DRX cycles and RRM measurement relaxation reduced power consumption, especially in idle/inactive states. Charging differentiation was supported via new requirements for core network functions.  
In Release 17, 3 GPP extended NR operation to 71 GHz, introducing a new unlicensed band, n263 (57-71 GHz). Accordingly, the FR2 frequency range was revised to be 24.25-71 GHz, and was further divided into FR2-1 and FR2-2, covering 24.25 GHz to 52.6 GHz and 52.6 GHz to 71 GHz, respectively. Subcarrier spacings of 120 kHz, 480 kHz, and 960 kHz were supported, enabling channel bandwidths up to 2 GHz. Features included dynamic spectrum access (LBT and non-LBT modes), beam management, multi-slot PDCCH monitoring, enhanced PUCCH formats, and HARQ timing optimizations. CA with FR1 anchors and intra-band contiguous aggregation were supported.
# A Multibody Model Calibration Method for Vehicle Misuse Testing
## 4 Nonlinear Parameter Calibration Using the Modified Quarter-Vehicle Model Analysis
### Equivalent Obstacle Parameter Calibration by Obstacle Contact Stage
With the natural circular frequency of the system \(\omega_{0}=\sqrt{(k+k_{\text{t}})/m}\) with two springs, \(Z\) is solved as  
\[Z=\frac{k_{\text{t}}v_{\text{e}}}{s^{2}(ms^{2}+k+k_{\text{a}})}=\frac{k_{\text {t}}v_{\text{e}}}{ms^{2}(s^{2}+\omega_{0}^{2})}=\frac{k_{\text{t}}v_{\text{e} }}{m\omega_{0}^{2}}\Bigg{(}\frac{1}{s^{2}}-\frac{1}{s^{2}+\omega_{0}^{2}} \Bigg{)}=\frac{k_{\text{t}}v_{\text{e}}}{k+k_{\text{t}}}\Bigg{(}\frac{1}{s^{2} }-\frac{1}{\omega_{0}}\frac{\omega_{0}}{(s^{2}+\omega_{0}^{2})}\Bigg{)}, \tag{36}\]  
According to the relation \(z(t)=\mathcal{L}^{-1}(Z(s))\), the solution of the forced vibration is obtained as  
\[z=\frac{k_{\text{t}}v_{\text{e}}}{k+k_{\text{t}}}\Bigg{(}t-\frac{1}{\omega_{0 }}\sin(\omega_{0}t)\Bigg{)}=\Bigg{(}1-\frac{1}{c_{\text{t}}}\Bigg{)}v_{\text{e }}\Bigg{(}t-\frac{1}{\omega_{0}}\sin(\omega_{0}t)\Bigg{)}. \tag{37}\]  
The maximum acceleration of the mass is then  
\[\ddot{z}_{\text{max}}=\Bigg{(}1-\frac{1}{c_{\text{t}}}\Bigg{)}v_{\text{e}} \omega_{0}. \tag{38}\]  
Figure 8: A single-DOF mass–spring system as a solution for studying the characteristics of the forced vibration. The displacement \(z(t)\) also occurs at the upper point of the tire spring. Therefore, in the modified quarter-vehicle model, we utilize the maximum acceleration of the wheel's center as the value for \(\tilde{z}_{\text{max}}\) Equation (38) instead. As \(\omega_{0}\) is the natural circular frequency of the system, we take \(\omega_{0}=\omega_{+,\textbackslash}\) in the modified quarter-vehicle model instead. That is,  
\[v_{\text{e}}=\frac{\tilde{z}_{\text{max},\textbackslash}\textbackslash{1}}{ \omega_{+,\textbackslash}}\cdot\frac{c_{\text{t}}}{c_{\text{t}}-1}. \tag{39}\]  
Upon examining the acceleration response curve for stage 1 in Figure 6b, the current vehicle obtains \(\tilde{z}_{\text{max},\textbackslash}\textbackslash{1}\approx 12\)g, where \(g\)= 9.8 m/s is the unit gravity acceleration. With \(c_{\text{t}}=3.86\) and \(\omega_{+,\textbackslash}\textbackslash{3}=92.40\) rad/s, \(v_{\text{e}}=1.57\) m/s is obtained. During the obstacle contact time interval of 0.035 s, the equivalent vertical displacement of the wheel's center is 55 mm, which is 55% of the speed bump's height.
# RIS-Assisted High-Speed Communications with Time-Varying Distance-Dependent Rician Channels
## Appendix C Proof of Proposition 3  
It has already proven in Proposition 2 that \(h(t)\) follows a complex Gaussian distribution with expectation \(\mu_{h}(t)\) and variance \(\sigma_{h}^{2}(t)\). Thus, we have  
\[\frac{|h(t)|^{2}}{\sigma_{h}^{2}(t)}\sim\chi^{2}(\
u,\xi(t)), \tag{31}\]  
where \(\chi^{2}(\cdot)\) denotes non-central chi-squared distribution with degrees of freedom \(\
u=1\) and non-centrality parameter \(\xi(t)=|\mu_{h}(t)|^{2}/\sigma_{h}^{2}(t)\). With the corresponding cumulative distribution function, outage probability \(\text{Prob}_{\text{out}}(t)\) is given by  
\[\text{Prob}_{\text{out}}(t)=1-Q_{\frac{1}{2}}\bigg{(}\sqrt{\xi(t)},\sqrt{ \gamma_{0}(t)}\bigg{)}, \tag{32}\]  
where  
\[\gamma_{0}(t)=\frac{\gamma_{\text{th}}}{\bar{\gamma}\sigma_{h}^{2}(t)}, \tag{33}\]  
and \(\gamma_{\text{th}}\) is a given SNR threshold, \(\bar{\gamma}=P_{t}/\sigma^{2}\). Note that \(Q_{u}(a,b)\) is the Marcum Q-function [24], i.e.,  
\[Q_{u}(a,b)=\frac{1}{a^{u-1}}\int_{b}^{\infty}x^{u}\exp\big{(}-\frac{x^{2}+a^{2 }}{2}\big{)}I_{u-1}(ax)dx, \tag{34}\]  
where \(I_{u-1}\) is the modified Bessel function of the first kind of order \(u-1\).
# Hybrid Sensing Platform for IoT-Based Precision Agriculture
## 4 Results
### Data Calibration
#### 4.2.2 Aerial Infrared Data Calibration Using Ground-Based Data--Experiment 5
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{3}{*}{**Cycles**} & **Solar** & **Wind** & **Wind Gust** & **Aerial and** & **Aerial and** \\  & **Radiation** & **Speed** & **Average** & **Ground-Based** & **Ground-Based** & **Ground-Based** \\  & **Average** & **Average** & **km/h** & **Infrared Data** & **Infrared Data** \\  & **w/m\({}^{2}\)** & **km/h** & **Correlation** & **Regression**\({\rm R}^{2}\) \\ \hline All & 357.1 & 13.3 & 20.5 & 0.91 & 0.83 \\ Morning & 74.3 & 9.1 & 14.1 & 0.89 & 0.79 \\ Afternoon & 757.7 & 14.9 & 21.3 & 0.75 & 0.56 \\ Evening & 252.1 & 15.2 & 24.7 & 0.92 & 0.85 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Aerial and ground-based infrared data comparison based on different time cycles and observation context variables. Figure 15: Original and calibrated aerial infrared data compared with ground-based data. ground-based temperature is 28.44, which is remarkably reduced compared with the aerial original plant temperature, which was 84.05. The obtained distance after calibration shows the minimum distance between aerial data and ground-based, which can be obtained using the linear regression model. The obtained line intercept and slope values can be automatically applied to future aerial data to obtain better data quality in comparison with ground truth.
# Performance Analysis of a 3D Wireless Massively Parallel Computer
## 1 Introduction
### Packet-Switching
#### 1.2.2 Cut-Through  
The main objective of this method is to start relaying a packet in an intermediate node before receiving the entire packet. This makes some overlap between using the input and output channels; and consequently, the link utilisation is improved, and overall parallel execution time is decreased. In practice, the output streaming starts after receiving the first 14 (or 64) bytes of incoming packet [49].  
Guaranteed continuation of data streams, in transmitter and receiver links, are needed; otherwise it may not yield satisfactory results. Handling of corrupt packets is another issue in cut-through method as the CRC (Cyclic Redundancy Check) sequence is normally the last part of a packet. This may lead to a decrease in effective link utilisation. This can be a bigger issue when dealing with wireless links in which the corruption may be detected only on the final receiver side. It may end up in a situation in which a packet is relayed in a whole chain of hops only to detect its corruption in the last hop. Another issue is the necessity of having the same transmission speed on both input and output channels; otherwise there would be no simultaneous streaming of data in and out of a node.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Ref.**} & **Data Rate** & **Range** & **Power** & **Energy/Bit** & **Energy/Bit/Dist** \\  & **(Gb/s)** & **(mm)** & **(mW)** & **(pJ/b)** & **(pJ/b/mm)** \\ \hline
[38] & 16 & 20 & 90 & 5.63 & 0.0141 \\
[39] & 11 & 14 & 70 & 6.4 & 0.0327 \\
[40] & 16 & 15 & 26.7 & 1.67 & 0.0074 \\
[41] & 25 & 120
_Article_  
**Optimization of a Six-Step Pressure Swing Adsorption Process for Biogas Separation on a Commercial Scale**  
**[PERSON] 1,*, [PERSON] 2, [PERSON] 3 and [PERSON] 4,*,6**  
* Center of Excellence on Petrochemical and Materials Technology, Chulalongkorn University, Bangkok 10330, Thailand
* Department of Chemical Engineering, Kasetsart University, Bangkok 10900, Thailand; [EMAIL_ADDRESS]
* RE Power Service Co., Ltd., Bangkok 10900, Thailand; [EMAIL_ADDRESS]
* Institute for Environment, Health, and Safety, Belgian Nuclear Research Centre (SCK CEN), 2400 Mol, Belgium
* Correspondence: [EMAIL_ADDRESS] (B.K.); [EMAIL_ADDRESS] (Q.T.P.); Tel.: +66-849-855-100 (B.K.); +32-1433-3240 (Q.T.P.)  
Received: 27 May 2020; Accepted: 6 July 2020; Published: 8 July 2020  
**Abstract:** Pressure swing adsorption (PSA) appears to be an effective technology for biogas upgrading under different operating conditions with low greenhouse gas emissions. This study presents the simulation of biomethane adsorption with the adsorption bed filled with a carbon molecular sieve (CMS). A six dual-bed six-step PSA process was studied which produced a high purity of biomethane. The design of the adsorption bed was followed by the real process of which the biomethane capacity was more than 5000 Nm\({}^{3}\)/h. For the adsorbent, a CMS-3K was used, and a biomethane gas with a minimum 92% purity was produced at 6.5 bar adsorption pressure. To understand the adsorption characteristics of the CH\({}_{4}\) and CO\({}_{2}\) gases, the Langmuir isotherm model was used to determine the isotherm of a mixed gas containing 55% CH\({}_{4}\) and 45% CO\({}_{2}\). Furthermore, the experimental data from the work of [PERSON] et al. were used to investigate the kinetic parameter and mass transfer coefficient. The mass transfer coefficients of two species were determined to be 0.0008 s\({}^{-1}\) and 0.018 s\({}^{-1}\) at 306 K for CH\({}_{4}\) and CO\({}_{2}\), respectively. The PSA process was then simulated with a cyclic steady state until the relative tolerance was 0.0005, which was then used to predict the CH\({}_{4}\) and CO\({}_{2}\) mole fraction along the adsorption bed length at a steady state. Moreover, the optimal conditions were analyzed using Aspen Adsorption to simulate various key operating parameters, such as flowrate, adsorption pressure and adsorption time. The results show a good agreement between the simulated results and the real operating data obtained from the company REBiofuel. Finally, the sensitivity analysis for the major parameters was presented. The optimal conditions were found to be an adsorption pressure of 6 bar, an adsorption time of 250 s and a purity of up to 97.92% with a flowrate reducing to 2000 Nm\({}^{3}\)/h. This study can serve as a commercial approach to reduce operating costs.  
**Keywords:** pressure swing adsorption; simulation; carbon molecular sieve; biogas; biomethane
## 2 Servitization
### Transaction Analysis  
Analysis of the Servitization process development in a company can be performed by examining the transition progress from a product organization to a product-service organization. [PERSON] proposed a model in which he provided a product-service-system (PSS) by establishing three basic classifications. These PSSs could be product-oriented, use-oriented, or result-oriented [42]. Afterwards, [PERSON] added integration-oriented and solution-oriented approaches in his research on the financial consequences of Servitization [43]. In addition [5], he later composed an illustration with an explicit analysis of the various elements (Figure 3) [5].  
In the first phase, a company focuses only on the selling of tangible goods, which are corroborated by services as add-ons and ownership changes at the point of sale. This is in line with the vertical integration of manufacturing companies [5, 42, 43].  
In the second phase, companies are still geared towards selling products, but several extra services are added, which are closely related to the product but not a necessity to use the product [5, 42, 43].  
In the third phase, services are added with no choice given to the customer in terms of deciding whether to use the service or not. This results in a bundling of a product and a service as an offering [5, 42, 43].  
In the use-oriented phase, the business model switches away from selling products, as the product stays under the ownership of the provider. This switch, implied by [PERSON] et al. [36], is illustrated in Figure 4[44, 45].  
[PERSON] divides this phase into three additional types of use-oriented services. The first type is the product lease, in which the customer leases the right to use the product. In the second type, the product-renting customer rents the right to use to product for a specific time period and must partially  
Figure 4: Switch from Ownership to access.  
Figure 3: Servitization Transition Approaches.  
share the product with other users. In the last type, the product is pooled to a large user base and is used by them simultaneously [42].  
In the last phase, the customer and the provider agree on a result, which must be provided. This solution-based approach is the final stage of Servitization. [PERSON] subdivides this phase into three types. First, the outsourcing type, which includes the outsourcing of entire departments or activities. In the second type, a customer agrees to pay according to a certain output of the product and a certain level of usage. The third type is based on the resulting product, and the provider is allowed to deliver the result using any given method [5; 42; 43].
## 4 LNSSCL Algorithm
### Algorithm Description  
Algorithm 1 describes the method of the LNSSCL algorithm; the pseudocode is shown below.  
Figure 3: Schematic of particle resurrection location selection.  
```
1:Graph \(G=(V,E)\)
2:The probability of preferential walk for particles \(\lambda\),
3:Particle energy increment \(\Delta\), Convergence factor \(\varepsilon\)
4:The number of communities \(K\), The set of communities \(C\)
5:\(t=1\)
6:\(K=2\)
7:repeat
8:for each particle \(k\)do:
9: calculate the initial positions of particles \(p^{(k)}(0)\) using Equation (10)
10:endfor
11:repeat
12:for\(k=1\) to \(K\)do:
13: calculate the particle's random walk probability \(P^{(k)}_{rand}(i,j)\) using Equation (4)
14: calculate the particle's preferential walk probability \(P^{(k)}_{pref}(i,j,t)\) using Equation (11), (12), and (13)
15: calculate the particle's walk probability \(P^{(k)}_{transition}(i,j,t)\) using Equation (3)
16: particles walk based on the walk probability and dynamically adjust the particle's control increment using Equation (15)
17:if\(E^{(k)}(0)\leq 0\):
18: particle performs the revival step by jumping to the within their control range that possesses the control capability for revival and re-energization.
19:endif
20:endfor
21:update \(\mathbf{Nu}(\mathbf{t})\), \(\overline{\mathbf{Nu}(\mathbf{t})}\), \(\mathbf{E}(\mathbf{t})\), \(\mathbf{S}(\mathbf{t})\)
22:\(t=t+1\)
23:until Equation (7) is satisfied
24: calculating and record the average maximum control capability indicator for particles \(\langle R(t)\rangle\) using Equation (8).
25:\(K=K+1\)
26:until\(\langle R(t)\rangle\) reaches its maximum value
27:assign the number of particles corresponding to step 22 to \(K\)
28:for each node \(v_{i}\in V\)do:
29:for each node \(v_{i}\in V\)do:
30:if the most frequently occurring neighboring community label is unique:
31: the label of node \(v_{i}\) is updated to the most frequently occurring community label.
32:else:
33: calculate the power score of each most frequent community \(Effect_{C_{k}}\) using Equation (16)
34: the label of node \(v_{i}\) is updated to the community label with the highest community effectiveness score
35:endif
36:endfor
37:return\(K-1\), \(C\)
```  
**Algorithm 1** LNSSCL algorithm
# A Comprehensive Survey of Recent Routing Protocols for Underwater Acoustic Sensor Networks
## 3 Routing Protocols for UWSNs
### EP-VIR-3 & BF-SPR-3  
Reference [60] proposes the energy-efficient path-based void hole and interference-free routing (EP-VIR-Three) and Bellman-Ford shortest path-based routing (BF-SPR-Three) routing protocols. These two proactive routing protocols adopt a sender-centric approach to improve reliability and reduce the likelihood of void occurrence. In order to improve the packet delivery ratio and avoid the void problem, a sender node chooses a subsequent relay node based on info about its three-hop neighbors. The info is based on difference in the depths of the current and the preceding node. In the case of BF-SPR-Three, the subsequent relay node is chosen using the Bellman Ford technique, which finds the shortest and  
Figure 14: Multi-layer perception (MLP) neural network model.  
fastest routes for routing data. Moreover, the binary tree method through horizontal layering is used to ensure reliable delivery of data. Additionally, this technique also resolves the routing loop problem. It prevents voids by taking into account the availability of 3-hop neighborhood of the forwarder (Figure 16). Moreover, energy consumption is reduced by selecting the node that is the least hops away from the sink node. The selection criteria for forwarding node also includes the number of neighbors of the candidate forwarder. The smaller number of neighbors of the candidate forwarder increases its weight in the cost function, thus minimizing energy consumption by minimizing participating nodes.
# Feature Integration Strategies for Neural Speaker Diarization in Conversational Telephone Speech
## 4 Results and Analysis
### Two-Speaker Scenario Performance
#### 4.1.1 GeMAPS Analysis
This optimized set consists of 52 parameters, including formants (14 features), fundamental frequency (10 features), frequency ratios (12 features), loudness parameters (10 features), and harmonics-to-noise ratio (6 features), while excluding voiced segments and jitter/shimmer features. This configuration achieves a DER of 13.93% compared to 13.60% with the complete set, demonstrating that we can maintain diarization performance while reducing computational complexity through informed feature selection. Figure 4: The degradation is measured as \(\Delta\)DER% when computing the mean of each feature group per audio file during inference.